Steve Truitt is an award-winning science fiction author, actor, producer, and musician. He received the prestigious Golden Eagle Award for his documentary series on Discovery. Steve's a space enthusiast and NASA history buff. He holds the unique record of having met five moonwalkers. Beyond his creative endeavors, Steve is also a coach and motivational speaker, recognized for his impactful work with the Best Motivational Book of the Year award for "Stop Waiting for Permission". Steve brings a wealth of experience and insight to discussions on AI and the future of work.

In this conversation, we discuss 

• How Steve got started in media and entertainment before branching out to other industries
• Industries being most impacted by AI
• The tricky ethics of AI and how to harness it as a tool that does more good than harm
• Why humanity is so fickle and prone to conflict 
• How leaders can stop the spread of misinformation with AI and what prevents them from doing so 
• Much more

Resources

Get Steve’s book, Mindset Chronicles

Additional episode you’ll enjoy 

AI fun fact 

Chris Herringshaw is the Chief Technology Officer at Janus Henderson Investors, overseeing all technology aspects and serving on the Executive Committee. With over 15 years at Citadel Investment Group, he led Global Infrastructure Technology as Managing Director. Chris founded Quova, now part of NuStar, and held roles including Vice President of Engineering and CTO. He holds a BS in computer systems engineering from the University of Michigan, and actively contributes to shaping technology's future through advisory roles and industry forums. 

In this conversation, we discuss:

• Venturing from entrepreneur to an established company.
• Chris Herringshaw's background in technology, including his experience at Janus Henderson Investors and as a CTO at venture-backed startups.
• How FinTech companies leverage the power of AI while mitigating risks associated with its unpredictable nature.
• Why human decision making still trumps AI and algorithmic based trading decisions in certain contexts.
• Predictions on where AI is headed in the next 12 months.
• The role of AI governance in ensuring the responsible and effective use of artificial intelligence.

Resource

Previous episode about an AI app platform that’s growing faster than OpenAI 

Learn more about Janus Henderson 

decoder.com/responsible-ai-now-has-an-iso-standard/#google_vignette">AI fun fact article

Dmitry Shapiro  is a serial entrepreneur who most recently founded and is the CEO of YouAi and the popular AI app-builder MindStudio. He has a bold vision to help you index your mind which we unpack in today's conversation. Previously, Dmitry founded and led GoMeta and  created the video sharing site Veoh in 2005 which  launched a few months after YouTube. Dmitry served as the CTO at MySpace before moving on to Google where was a Group Product Manager working on social graph, identity, and content discovery. Dmitry received his BS in EE from Georgia Tech.

In this conversation, we discuss:

• The New York Times versus OpenAI and Microsoft copyright lawsuit and its implications for AI.
• The challenges and stakes for publishers when facing AI applications using copyrighted material.
• Dmitry Shapiro's entrepreneurial journey and the vision behind MindStudio.
• The impact of generative AI on computing and its potential for revolutionizing work and home environments.
• Legal and ethical considerations surrounding AI, copyright, and fair use.
• The intersection of technology, venture capital, and innovation in shaping the future of AI applications.

Additional resources 

• Another episode to enjoy 
• Fun fact article 

As the Chief Product Officer at Alteryx, Suresh leads the product, engineering, design, and development teams that deliver innovative and scalable solutions for data science and analytics. He is also responsible for product pricing, packaging, and PLG strategies. Over the past 3 years, Alteryx has transformed into an analytics platform with market-leading end-to-end analytics solutions, covering the entire gamut of users from analysts to data engineers, developers, and data scientists.

With over 20 years of experience in the SaaS industry, Suresh has a proven track record of driving growth, customer satisfaction, and market leadership for cloud-based platforms and products.

In this conversation, we discuss:

• The ongoing debate between AI guardrails and user autonomy, referencing Mark Gimein's "spicy mayo problem" as a case study.
• Suresh Vittal's background, journey through analytics and AI, and his role as Chief Product Officer at Alteryx.
• Alteryx's mission of "analytics for all" and their focus on empowering users across technical and non-technical roles in data analytics.
• The integration of generative AI features into Alteryx's platform to simplify complex workflows and enhance collaboration among data professionals.
• Insights into AI-first data management strategies and the evolving landscape of AI-driven tools in the future of work.
• The importance of governance and transparency in AI-powered analytics, ensuring clarity and understanding across complex data workflows for improved decision-making.

Additional resources: 

Suresh’s LinkedIn page

Related episode you might enjoy about responsible AI use

AI fun fact article in the Atlantic 

Ben Kus is the chief technology officer at Box, where he’s responsible for developing Box's technology vision and strategy.  Previously, Ben was the VP of product management at Box. Before joining Box, he was the co founder and CTO of Subspace, an enterprise security solution that was acquired by Box. 

Ben’s held various leadership positions, including chief architect for IBM and senior director of technology for BigFix.  

What we discuss:

• The role of generative AI in enhancing productivity and unlocking new use cases within enterprises, focusing on content management.
• Ben shares insights into Box's innovative culture and compares it to other companies like IBM, highlighting the company's approach to technology and innovation.
• The discussion touches on responsible AI use, regulatory considerations, and Box's commitment to transparency and compliance.
• Ben addresses concerns about AI's impact on jobs, emphasizing AI's role in augmenting productivity rather than replacing human jobs.
• Future trends in AI, including personalized AI assistance and potential advancements in AI capabilities, are explored.
• The conversation ends with a fun anecdote about Box's CEO, Aaron Levie, known for his magic tricks and the company's unique culture of bringing your own self to work.

Additional resources

• Ben’s LinkedIn 
• Other episodes you might enjoy about the future of Media & AI
• Fun fact: how much energy is required to create an image with generative AI? 

Neil Mandt is a Hollywood entrepreneur, a five-time Emmy winner, and producer of the 2022 Golden Globes.  A pioneer in AR and VR technology, and a pro sports owner, since getting his start in Hollywood at age 10, there's almost no award he hasn't received, and almost no new form of media he hasn't tested and improved. 

What we cover

• In this conversation, Neil shares insights into the evolving landscape of Hollywood and the role of AI in content creation and consumption.
• Neil discusses the potential of AI to democratize content creation, enabling individuals to produce high-quality movies and TV series with minimal resources.
• We delve into the challenges and opportunities presented by AI in the entertainment industry, including the gamification of user engagement and personalized content experiences.
• Neil emphasizes the importance of embracing AI tools for content creators to stay competitive and adapt to changing consumer preferences.
• Neil highlights the transformative potential of augmented reality (AR) and virtual reality (VR) technologies in enhancing the content consumption experience.
• Neil provides valuable insights into the skills required for content producers to thrive in a future where AI-driven, interactive storytelling becomes the norm.
• And much more.

Additional resources

• Neil’s site — Neilmandt.com 
• Course on making it in media and entertainment — https://neilmandt.com/course
• Other episodes you might enjoy — https://aiandthefutureofwork.buzzsprout.com/520474/14689727-babak-hodjat-cto-of-ai-at-cognizant-on-creating-siri-and-the-evolution-of-ai

Babak is the CTO of AI at Cognizant, the 34 billion market cap provider of tech services with more than 350, 000 global employees. He's the former co-founder and CEO of Sentient, a business responsible for the core technology behind the world's largest distributed artificial intelligence system. Before co-founding Sentient, Babak co-founded and was the CTO and a board member of Dejima where he developed the foundational technology that ultimately became Apple's Siri. 

He's the primary inventor of Dejima's patented technology. Babak has 31 granted or pending patents, is a published author, and is one of the most respected thought leaders in AI.  He holds a PhD in machine intelligence from Kyushu University in Fukuoka, Japan. 

In our conversation, we discuss: 

• The recent executive order on AI regulation issued by the Biden administration, exploring its key themes such as the development of a national registry for foundational large language models and safety test result sharing by vendors.
• Babak shares insights into the challenges and engineering intricacies involved in developing and scaling AI systems, emphasizing the importance of understanding the fundamental differences between large language models and human intelligence.
• The concept of responsible AI and the urgent need for defining unambiguous ethical standards, with Babak expressing concerns about AI potentially being used for destructive or malicious purposes in the wrong hands.
• Babak's experience as a pioneer in developing foundational technologies for Siri
• The limitations and expectations surrounding large language models shed light on the challenges of fine-tuning and reinforcing these models, as well as the misconceptions related to their learning capabilities during interactions.
• The concept of active ontology and its role in the early development of Siri, highlights the revolutionary approach that focused on modeling functionality and ontology first, offering insights into the evolution of natural language technology over the past 25 years.

Additional resources

• Babak's LinkedIn — https://www.linkedin.com/in/babakhodjat/
• Another episode you might enjoy — https://aiandthefutureofwork.buzzsprout.com/520474/14341487-navrina-singh-founder-ceo-of-credo-ai-discusses-ai-governance-ethics

Richie Cotton and his co-host Adel have published over 150 episodes of the DataFramed podcast with some amazing guests. Richie's also a data evangelist for  DataCamp and a data scientist by training. He helps train DataCamp students and has been instrumental in the company's success. DataCamp has trained data teams at more than 2,500 companies, including 80 percent of the Fortune 100. Richie has degrees in Math from the University of Warwick and the University of York. 

In our conversation, we discuss: 

• The Evolving Role of Data Scientists: Richie Cotton shares insights into the changing landscape of data science and how the role of data scientists is expected to transform in the next decade, emphasizing the increasing accessibility of powerful tools.
• Ethical Considerations in AI: we delve into the ethical implications of artificial intelligence, exploring the responsibility of data scientists and AI practitioners in addressing issues such as bias, transparency, and privacy in their work.
• Future Skills for Data Scientists: Richie discusses the essential technical skills for data scientists, including the ongoing debate between Python and R, and highlights the importance of staying adaptable as technology evolves.
• AI's Impact on Business Operations: we explore the potential impact of AI on various industries, focusing on business operations and efficiency, providing valuable insights for professionals looking to harness AI for strategic advantages.
• Predictions for Artificial General Intelligence (AGI): Richie shares intriguing perspectives on the timeline for achieving artificial general intelligence, citing predictions that AGI might become a reality in the 2030s and discussing the potential implications of such advancements.
• Teaching and Learning Data Science at Scale: we shed light on Richie's experience at DataCamp, where he has been instrumental in teaching data science to hundreds of thousands of individuals, highlighting the platform's mission to make data science education accessible globally.

Additional resources

• Listen to Richie’s podcast — https://www.datacamp.com/podcast
• Other episodes you might enjoy — https://aiandthefutureofwork.buzzsprout.com/520474/14341487-navrina-singh-founder-ceo-of-credo-ai-discusses-ai-governance-ethics

Matt Martin is on a mission to help the world make time for what matters. He founded Clockwise in 2016 to fix the time problem.

Since then, he and the team have raised 76 million from exceptional investors, including Greylock, Cotu, Excel, Bain, and a common investor, the Slack Fund.  More than 15, 000 organizations run Clockwise. Matt was also an engineering leader at Relate IQ before Salesforce acquired it for $390 million in 2014.

In our conversation, we discuss: 

• Interesting ways to improve your productivity
• New developments in GPT-4 supporting productivity
• Challenges of time management and the impact of AI in reshaping scheduling practices, emphasizing the importance of tools like Clockwise in optimizing work schedules.
• Lesson in entrepreneurship from Matt
• How AI can be leveraged to make your work more fulfilling
• Much more

Prasad Kawthekar is the Co-Founder & CEO of Dashworks, an all-in-one AI search assistant. It enables users to find any document, message, or email and to accelerate a team's productivity. With over 40+ integrations, Dashworks enables teams to find and organize their internal knowledge across apps from one place and leverage their collective expertise.

In our conversation, we discuss: 

• The historical evolution of enterprise search tools
• The challenges to enterprise search adoption: such as API integration complexities persist, hindering widespread adoption
• The role of Generative AI in search
• Limitations of current AI models and what the future holds for them.
• What are some considerations for future AI development?
• The potential of retrieval-augmented generative AI (RAG) in providing accurate and factual responses, while also acknowledging its limitations and potential for further evolution

Additional resources: 

• Visit Dashworks: https://www.dashworks.ai/
• Another episode you might like: https://aiandthefutureofwork.buzzsprout.com/520474/14464391-dr-eric-siegel-founder-of-machine-learning-week-on-6-steps-to-usher-in-successful-ml-projects

Atif has blazed trails in Silicon Valley and the Fortune 500 for over 25 years. After rising through digital native companies like Amazon, Yahoo!, and AOL, Atif held C-suite roles at McDonald’s, Volvo, and MGM Resorts. He oversaw thousands of employees as a global P&L, transformation, and innovation leader. 

Rafiq was the first Chief Digital Officer in the history of the Fortune 500, a pioneering role he held at McDonalds, and he rose to the President level in the Fortune 300. While leading business units, teams, and growth for companies, Atif has built a large following as one of today’s top management thinkers. Over 500,000 people follow his ideas about management and leadership on LinkedIn, where he is a Top Voice, and his newsletter Re:wire has over 100,000 subscribers. Atif has also been nominated 

Atif is passionate about helping companies push boldly into the future. He accomplishes this through Ritual, a software app revolutionizing how teams innovate and problem-solve, and through his work as keynote speaker, Board member, and CEO advisor. 

Listen and learn

• What’s broken about the decision-making process in large companies
• What is the decision sprint process 
• How will team formation/team structure change as a result of AI?
• How do we measure the quality of the output of a decision sprint?
• What are the smartest ways to engage generative AI in the decision sprint process?
• How do you reasonably deal with the fear of AI replacing your job?
• Much more

Resources

— Buy the book — https://www.decisionsprint.com/

— Ritual — https://www.ritual.work/—  Listen to a related episode — https://www.buzzsprout.com/520474/14158168-bruce-feiler-best-selling-author-ted-celebrity-tv-personality-and-new-york-times-columnist-discusses-navigating-life-transitions

Dr. Eric Siegel is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI World, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die," which has been used in courses at hundreds of universities, as well as "The AI Playbook: Mastering the Rare Art of Machine Learning Deployment." 

Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate *computer science* courses in ML and AI. Later, he served as a *business school* professor at UVA Darden. Eric has appeared on numerous media channels, including Bloomberg, National Geographic, and NPR, and has published in Newsweek, HBR, SciAm blog, WaPo, WSJ, and more.

Listen and learn

• How he’s progressed in the field of machine learning over 30 years
• 6-step process to usher in machine learning programs from conception to deployment 
• What 3 things non-technical people in business should know about how machine learning works & delivers value
• How to know when to use classical machine learning vs generative AI to solve a data problem
• How to mitigate the impact of human bias in shaping AI

Resources

• Purchase "The AI Playbook" — http://www.bizML.com 
• Scott Zoldi episode —https://feeds.buzzsprout.com/520474.rss

Juliette Powell is the founder and managing partner of Kleiner Powell International [KPI], a New York City-based consultancy. As a consultant at the intersection of responsible technology and business, she has advised large companies and governments on how to deal with the accelerating change underway due to AI-enabled technological innovation coupled with shifting social dynamics and heightened global competition. She’s also on the faculty at New York University and teaches in the Interactive Telecommunications Program. 

Art Kleiner is a writer, lecturer, and consultant with a background in management, interactive media, corporate environmentalism, scenario planning, and organizational learning. He is a co-author (with Pete Senge et al.) of the best-selling Fifth Discipline Fieldbook, The Dance of Change, and Schools That Learn; and author of Who Really Matters: The Core Group Theory of Power, Privilege, and Success. Since 1986, he has taught in New York University's Interactive Telecommunications Program.

Juliette and Art co-authored a new book, The AI Dilemma: 7 Principles for Responsible Technology.

Listen and learn

• How Juliette and Art started their careers 
• The Principles of Responsible Technology 
• What could happen if AI became sentient? 
• How can we prevent AI from reinforcing negative biases and discrimination?
• How people and organizations can practice better ethics when leveraging AI?
• What will it take to engrain more ethical, equity-oriented thinking into business education?  
• Much more

References in this episode…

• Juliette and Art's website
• Gary F. Bengier discusses AI’s impact on humanity

Dave Kellogg is an advisor, director, consultant, angel investor, and blogger focused on enterprise software startups.  He’s the executive-in-residence (EIR) at Balderton Capital and the principal of his own eponymous consulting business.

He brings an uncommon perspective to startup challenges having 10 years’ experience at each of the CEO, CMO, and independent director levels across 10+ companies ranging in size from zero to over $1B in revenues.

Dave also authors the Kellblog which covers topics related to starting, leading, and scaling enterprise software startups including strategy, marketing, positioning, messaging, management, go-to-market, SaaS metrics, and venture capital financing.

Listen and learn

• How Dave did with last year's predictions
• What's ahead for the venture capital ecosystem in a post ZIRP environment
• How CIOs are investing in automation
• What to expect from the big LLM vendors
• What's ahead for AI and copyright protection in 2024
• And much more...

References in this episode…

• Kellblog — https://kellblog.com/
• Amr Awadallah, Vectara CEO, on AI and the Future of Work

Navrina Singh is the Founder and CEO of Credo AI, a Governance SaaS platform empowering enterprises to deliver Responsible AI. A technology leader with over 18+ years of experience in Enterprise SaaS, AI and Mobile, Navrina has held multiple product and business leadership roles at Microsoft and Qualcomm. Navrina and the team have been on a mission to help organizations create AI that adheres to the most ethical standards since March 2020. Credo has raised over $13 million from an impressive list of investors that includes Decibel Partners, Sands Capital Ventures, and the AI Fund, among others. Navrina is a member of the national AI advisory committee and is a world Economic Forum global leader. Prepare to be inspired.

Listen and learn

• If Navrina ran the world, how she’d regulate AI 
• How to incorporate consumer feedback & inclusive practices into the AI development process
• How companies can start creating trustworthy, ethical AI 
• How Navrina is empowering companies to deliver responsible AI at scale
• Criteria to consider for combatting algorithmic bias
• How to deal with the fear of being replaced by machines
• Navrina's advice to young entrepreneurs

Adam Wenchel is the CEO of Arthur, a company with a platform that gives you an immediate comprehensive AI performance solution across LLMs, Computer Vision, Tabular Data, and NLP. 

Adam and the team have been making AI observable for almost 5 years with Arthur. Arthur has raised over $60 million from a legendary group of investors including Index Ventures, Greycroft Partners, Work-Bench, and others. An equal list of impressive customers they’ve served includes Humana and Plaid, among others. 

Listen and learn

• How Adam started his career in AI
• How he helped map out Capital One’s early AI strategy 
• The value of evaluating AI model performance 
• How Arthur launched its first LLM-specific product and what the team learned 
• How to monitor the performance of an LLM model in production and which questions to ask when evaluating it 
• The lessons from growing a startup that nobody talks about 

References in this episode…

• Arthur’s website - https://www.arthur.ai/

Sean Behr is the CEO of Fountain, the company transforming the hiring process for hourly workers. Sean and the team have helped more than 80M applicants in 75 countries at places like Stitch Fix, sweetgreen, and gopuff. Fountain has raised $225M to date most recently through a $100M series C last June from an amazing list of investors including B Capital Group, SoftBank, DCM, and Uncork Capital.

Sean joined Fountain as CEO in 2020 after founding fleet infrastructure platform Stratim, serving as SVP of Adap.tv through its acquisition by AOL, and holding various management roles at Shopping.com.

Listen and learn...

1. How Sean is creating opportunities for frontline workers around the world
2. What's uniquely challenging about hiring frontline vs. knowledge workers
3. How long before robots will replace human frontline workers
4. The ethical implications of using AI in hiring
5. What biases are embedded in the hiring process... without AI
6. Why the future of hiring... is more human thanks to AI

References in this episode...

1. May Habib, Writer CEO, on AI and the Future of Work
2. Josh Bersin, HRTech pioner, on AI and the Future of Work
3. Why every organization needs a Chief Ethics Officer

Wipro is one of the largest providers of tech and tech services in the world with more than 250,000 employees. It was started in 1945 and is now the third largest software company in India with a market cap of more than $27B.

We're lucky to be joined today by the leader driving Wipro's technology vision. Subha Tatavarti joined Wipro as Chief Technology Officer in March 2021 after a distinguished career in tech leadership roles at companies like Walmart and PayPal where she led the product, data, and infrastructure teams. Subha holds a Masters in Computer Science. She's an avid hiker and enjoys trail running and books on philosophy.

Listen and learn...

1. What Wipro's 1,400+ enterprise customers expect from gen AI
2. What are the top use cases for enterprise AI in 2024
3. Why the quality of AI-generated code has surprised Subha
4. One year in... how does Subha describe the state of enterprise adoption of gen AI
5. What is holding back broader adoption of gen AI
6. Why regulatory frameworks alone are sufficient to reign in the bad actors
7. Early adopting industries and geographies you wouldn't expect
8. Subha's advice to CIOs and CTOs about how to pick the right business problem to solve with AI
9. Subha's vision for the future of human interaction

References in today's episode...

• Durga Malladi, Qualcomm SVP, on AI and the Future of Work
• newsletter.beehiiv.com&utm_medium=newsletter&utm_campaign=what-is-trending-in-ai-research-open-interpreter-avis-tinyllama-llasm-qwen-vl-and-qwen-vl-chat-what-is-trending-in-ai-tools">AI classifiers can't distinguish human from AI-generated content
• Wipro's billion-dollar investment in AI 
• The Wipro ai 360 hub
• Wipro's approach to responsible AI
• The Azim Premji Foundation

We've had amazing unicorn CEOs recently on this podcast but today's a first. Wade Foster, CEO and co-founder of Zapier grew his company to a $5B valuation in 2021 on a $1.3M raise in 2012. Let that sink in. The power of product-market fit and listening to your customers is impossible to overstate.

Wade and his co-founders Bryan and Mike launched Zapier in 2012 as part of the YC S12 batch.

The company has grown to more 800 employees in 40 countries and the product is used by 2.2M businesses and integrates more than 5,000 apps that have been used to create more than 25 million zaps, or automated workflows.

Listen and learn...

1. Wade's humble path from an internship in Columbia, MO... to a $5B unicorn
2. A simple problem: the Zapier origin story
3. The Zap that started it all...
4. Voice-first Zaps? Maybe!
5. The future of the "citizen developer"... no-code interfaces + enterprise security
6. Why all the new GenAI apps will create more need for Zaps
7. The Zapier LLM architecture
8. How to find product-market fit... from an expert
9. Creating a company that's a verb: how "Zapier" got its name
10. Wade reflects on his success and the entrepreneurial journey
11. What's ahead for Wade and Zapier

References in this episode...

1. Vijay Tella, Workato CEO, on AI and the Future of Work
2. Amr Awadallah, Vectara CEO, on AI and the Future of Work
3. ChatGPT for the enterprise: what's included

BRUCE FEILER is one of America’s most thoughtful voices on contemporary life. He is the author of seven New York Times bestsellers, including LIFE IS IN THE TRANSITIONS,  THE SECRETS OF HAPPY FAMILIES, and COUNCIL OF DADS. His three TED Talks have been viewed more than four million times, and he teaches the TED Course HOW TO MASTER LIFE TRANSITIONS. His latest book, THE SEARCH: Finding Meaningful Work in a Post-Career World (May 2023), is a bold new roadmap for finding meaning and purpose at work.

A longtime columnist at the New York Times, Bruce now writes the popular newsletter THE NONLINEAR LIFE. He has appeared in numerous publications, including The New Yorker, The Wall Street Journal, Harvard Business Review, and Gourmet, where he won three James Beard Awards. A former circus clown, he has been the subject of a Jay Leno joke and a JEOPARDY! question, and his face appears on a postage stamp in the Grenadines.

Listen and learn...

1. Bruce's search for meaning in the face of setbacks and challenges
2. How to reconcile our complicated relationship with work and our personal search for meaning
3. Bruce's "three lies and a truth about work"
4. How to identify what brings you meaning
5. The four historical changes in the nature of work
6. Why it's important to "ignore the lessons of your parents"
7. The one thing we know about AI and the future of work

References in this episode...

• Bill Davidow on AI and the Future of Work
• Dr. Meredith Broussard on AI and the Future of Work
• Linda Rottenberg on AI and the Future of Work
• How soon before LLMs replace human comedians?

We've met future of work visionaries recently like Gary Bolles, Dr. John Boudreau, Mark McCrindle, and Josh Bersin. All have shared unique perspectives on how AI is redefining the employee experience. Today's guest belongs on that Mt. Rushmore of future of work luminaries.

Josh Drean is Co-founder & Director of Employee Experience at The Work3 Institute, AI + Work Advisor at the Harvard Innovation Labs, and Co-author of Employment is Dead (Harvard Business Review Press, 2024)

His work has been featured in Harvard Business Review, Forbes, Fast Company, and The Economist and he has made appearances on The Today Show, NBC, and FOX Business. He speaks internationally to bring work tech insights to digital-first leaders who value human-centric work experiences.

Listen and learn...

1. How AI is changing our relationship with work
2. Work 3... vs. work 1 and work 2
3. How the metaverse is enabling a global talent marketplace
4. What RTW is doing to the relationship between employees and employers
5. Why "employment is dead"... but we'll soon enjoy work more as a result
6. "There are two camps... those who are embracing AI... and those who will become obsolete."
7. Why employee surveillance is the wrong approach
8. Why "passion is future-proof"

References in this episode...

1. Josh Bersin on AI and the Future of Work
2. Gary Bolles on AI and the Future of Work
3. James Lawton from Zebra on AI and the Future of Work
4. AI Snake Oil by Princeton Professor Arvind Narayanan
5. Josh Drean on YouTube

Tom Wheeler served as the 31st Chairman of the Federal Communications Commission after being appointed to the role by President Obama in November 2013. His chairmanship has been described as “The most productive Commission in the history of the agency.”

Prior to that, he was a venture capitalist and, among other roles, the CEO of the Cellular Telecommunications & Internet Association (CTIA) where we first met in 2001. He is the only person to be elected to both the Cable Television Hall of Fame and the Wireless Hall of Fame, which led President Obama to proclaim him “the Bo Jackson of telecom.” Additionally, Tom is an award-winning author, a sought after speaker about topics ranging from leadership to net neutrality, and a visiting fellow at The Brookings Institution.

Listen and learn:

1. Why today's Digital Age is reminiscent of the early 20th century Gilded Age
2. How owners of today's digital pathways make rules that govern privacy and safety
3. What does history teach us about how can we take back control of our data from Big Tech
4. How to make capitalism work for everyone
5. Why AI is triggering an awareness of the impact of Big Tech on our lives
6. What's different about regulatory models in the digital era
7. Why we need a new agile, digital-first agency to regulate Big Tech
8. How to regulate Big Tech without stifling innovation

References in this episode:

• Mark McCrindle on AI and the Future of Work
• Pew Research: 68% of US adults don't trust Big Tech to self-regulate
• Techlash: Who Makes the Rules in the Digital Gilded Age
• Scientific Management by Frederick Taylor
• Which tasks is AI being used to do at work today?

Today’s guest is a General Partner at Foundation Capital, one of the most iconic venture capital firms in the world. Foundation has found and funded companies like Netflix, Solana, Jasper, and the list goes on.

Joanne Chen began her investing career at Foundation in 2014 and has sourced and advised an incredible group of companies including Tonkean, Tubi, and CaptivateIQ. Joanne received her BS in EE and CS from Cal and her MBA from the University of Chicago. She's also a popular TEDx speaker.

Today we get a master class on how the best are adapting to one of the most challenging venture investing climates in decades. Joanne and I met on a panel discussion a few months back . I've been looking forward to introducing her to our community.Listen and learn...

1. Joanne's perspective on the euphoria surrounding GenAI
2. What's different about investing in AI post-ChatGPT
3. Why AI tools are increasing the pace of innovation
4. The difference between crypto and AI investing
5. What responsible AI means to Joanne
6. Joanne's advice to "AI entrepreneurs" pitching venture investors
7. How long before AI will take Joanne's job

References in this episode...

1. Ashu Garg on AI and the Future of Work
2. Joanne's TEDx talk: Confessions of an AI Investor
3. Joanne's TEDx talk: Why AI Promises a Brighter Future
4. The ethical implications of using AI in healthcare

Today’s guest is one of the most respected thought leaders in the HR and HRTech space. Josh Bersin’s name is synomous with HR thought leadership. He first started covering the space in 2001 before selling Bersin & Associates to Deloitte in 2012. His current namesake company, The Josh Bersin Company, hosts the popular annual conference Irresistible and is a prolific publisher of content related to the future of work, talent management, corporate learning, and leadership.

Josh is also the author of the popular book Irresistible: The Seven Secrets of the World's Most Enduring, Employee-Focused Organizations, which was published in 2022. Oh, and he also hosts a great podcast. I always enjoy his candid commentary on HRTech.

Listen and learn...

1. The single employee behavior that most impacts productivity
2. What people practice surprised Josh most about what distinguishes leading from lagging companies
3. How "taking care of people" saved many companies during the pandemic
4. The HRTech innovation that improves the employee experience most
5. Why employees took back power from employers... and insisted on better tools
6. Where are there opportunities to innovate in HRTech
7. How AI "meets people in the flow of work"
8. How talent intelligence is assisting HR leaders
9. Why employees shouldn't feel threatened by AI
10. Why what Josh calls "organizational ingenuity" is more important than having the best tech skills
11. The future of work, according to Josh

References in this episode...

• Mark McCrindle on AI and the Future of Work
• Dr. John Boudreau on AI and the Future of Work
• Gary Bolles on AI and the Future of Work
• Josh's book Irresistible
• Josh's podcast
• Why are LLMs getting dumber?

Amr and I met on a genAI panel and everything he said was both insightful and contrarian. Immediately, I knew I wanted to introduce him to you. Amr is a legend in the search space who, by the way, also founded Cloudera which went public in 2017 at a valuation of over $5B.

Dr. Amr Awadallah is a luminary in the world of information retrieval. He's the CEO and cofounder of Vectara, a company that is revolutionizing how we find meaning across all languages of the world using the latest advances in Deep Neural Networks, Large Language Models, and Natural Language Processing. He previously served as VP of Developer Relations for Google Cloud. Prior to joining Google in Nov 2019, Amr co-founded Cloudera in 2008 and as Global CTO. He also served as vice president of product intelligence engineering at Yahoo! from 2000-2008. Amr received his PhD in EE from Stanford University, and his Bachelor and Masters Degrees from Cairo University, Egypt.

Listen and learn...

1. How Amr discovered the power of "talking to software" via LLMs while at Google
2. About the history of new computing modalities
3. About the current state of generative AI
4. The technical explanation for hallucination in LLMs
5. How do we mitigate bias in LLM models and prevent copyright infringement
6. Why a semantic understanding of queries is the next frontier in search
7. The challenge faced by search providers of making money incorporating ads into LLM-based answers
8. How "grounded search" will fix the hallucination problem
9. What is a "fact" in the era of ChatGPT?
10. How long before we have "antivirus sofware for fact-checking" genAI propaganda
11. How should AI be regulated... and who is responsible for AI regulation
12. The next big idea in genAI Amr and I are ready to fund
13. Amr's advice to entrepreneurs... and to himself

References in this episode...

1. Eric Olson, Consensus CEO, on AI and the Future of Work
2. D Das, Sorcero CEO, on AI and the Future of Work
3. Seth Earley, Earley Information Science, on AI and the Future of Work
4. ChatGPT for searching scientific papers

Dr. John Boudreau is a luminary in the future of work academic community. He has published more than 50 books and articles. His scholarly research is published in Management Science, Academy of Management Executives, Journal of Applied Psychology, and Personnel Psychology. Features on his work have appeared in Harvard Business Review, The Wall Street Journal, Fortune, Fast Company and Business Week, among others. 

Dr. Boudreau helped  establish and then directed the Center for Advanced Human Resource Studies (CAHRS), at Cornell University, where he was a professor for over 20 years, before his current position as Research Director for the Center for Effective Organizations at the University of Southern California.Thanks to friend of the podcast David Creelman for the intro to Dr. Boudreau!

Listen and learn...

1. How Dr. Boudreau got his start as an academic in HRTech
2. What inspired Dr. Boudreau to make work life better for employees everywhere
3. How Dr. Boudreau defines work (the most enlightened definition we've heard)
4. How to build high-functioning teams
5. Why diverse teams don't perform better
6. How alternative work and workers are redefining the labor force
7. Why jobs don't equal work and degrees don't equal jobs
8. What does it mean to be human when your colleague is a bot
9. Why ATM machines led to more human bank tellers being hired
10. About the rise of internal talent marketplaces
11. Which skills AI will never automate

References in this episode...

• Mark McCrindle on AI and the Future of Work
• Bryan Talebi from Ahura on AI and the Future of Work
• Kamal Ahluwalia from Eightfold on AI and the Future of Work
• Work without Jobs, Dr. Boudreau's most recent book
• The Center for Effective Organizations 
• Using AI as a co-pilot for songwriting

Today's guest has been bringing families together online since 1997 when he founded Ancestry.com which has served more than 13 billion profiles, amassed 40 billion people records, and generated over a billion dollars in revenue. He followed that up with FamilyLink which he founded in 2007 and today has more than 50 million users.

For the past several years, Paul Allen has been on a new adventure having founded Soar.com in 2017. He and the team are connecting employees to stories from trusted sources to help them make better, more informed decisions.

Soar indexes millions of hours of video and audio content in domains as diverse as academic lectures, political hearings, and stump speeches. Not surprisingly, he and the team are using AI to make all that content discoverable and accessible.

Paul is a sought after speaker, a director of the Human Justice Foundation, and is one of the most mission-driven entrepreneurs of our generation.

Listen and learn...

1. Paul's number one business lesson
2. How Paul "uplifts humanity" with AI
3. Why the "factory education system" doesn't work
4. Why AGI won't be the end of civilization
5. How an AI studio for audio transcription works
6. The role of CitizenGPT... and why it won't hallucinate
7. How AI is restoring lost human connections
8. How to detect and mitigate the danger of deepfake video content using a blockchain
9. What it means to be an ethical publisher of content in the age of AI
10. Paul's (not so obvious) secret to success

References in this episode...

• Guillermo Corea from SHRM on AI and the Future of Work
• The current state of AI ethics
• Dr. Sanchez' WHY Institute
• Sarah Allen, acclaimed author (and Paul's daughter)
• The autobiography of Booker T. Washington

Anyone who has ever hired a new employee knows how important and broken the background check process is. The experience is awful for candidates and employers. Plus, it's inherently unfair for under-represented and non-traditional candidates. Imagine a world where hiring the best people is easier and faster and all forms of verification data are provided automatically from trusted sources.

Today's guest is making that vision a reality. Denise Hemke is the Chief Product Officer at Checkr, the amazing company making employee screening more fair for everyone. Checkr has raised nearly $700M since its founding in 2014. Denise heads up product management, design, and program management after having served in various leadership roles at Workday including most recently GM for Analytics. Denise is also the San Francisco chapter lead for the excellent organization Products That Count started by friend of the podcast SC Moatti.

Listen and learn...

1. How to fix the broken background check process
2. How to give candidates with non-traditional backgrounds access to the labor force
3. How technology is making the hiring process more fair and helping workers get paid faster
4. How to use AI to reduce bias in hiring decisions
5. How AI used for background checks should be regulated
6. What Denise learned about building customer communities as a General Manager at Workday

References in this episode...

• Mustafa Suleyman's new Turing test
• Kamal Ahluwalia, former President of Eightfold, on AI and the Future of Work
• Giselle Mota from ADP on AI and the Future of Work

AI is here to accelerate the world's creativity. In fact, it's one of the things generative AI does best. Imagine a world where personalized campaigns help products you love find you. Today's guest did just that and he created Evolv AI to help brands connect with customers across all digital channels. 

Tyler Foster is the CTO of Evolv AI, a platform that helps brands improve conversion and experiment faster. He started the company with CEO Michael Scharff in 2019 and together they've grown it into an early leader in AI-first digital experimentation having helped brands like Safelite, DirectTV, and Verizon. Prior to Evolv AI, Tyler was the founding CEO and Chief Architect of Senient Systems and an early Software Engineer at Cloudera.

Listen and learn...

1. How a farmhand and SCUBA diver became an AI developer
2. How AI is helping brands target consumers
3. The tradeoff between personalization and data collection
4. How to eliminate bias in automated decisions
5. Will AI eliminate creative jobs?
6. How society needs to adapt to new definitions of work imposed by AI
7. Why we need to disconnect ideas from tools and processes
8. What does it mean that we're entering a "post-truth" era?
9. Why AI is more fair than humans

References in this episode...

• Meredith Broussard on AI and the Future of Work
• Diane Keng from Breinify on AI and the Future of Work
• Are AI-generated ads more or less effective?
• Evolv.ai

Tim Guleri has had a remarkable run at Sierra Ventures since 2001. He has invested in transcendent companies including Sourcefire and MakeMyTrip which both went public. Before that, Tim had a successful career as an entrepreneur and exec at companies like Scopus and Octane which was acquired by Epiphany in 2000.

Sierra has one of the strongest future of work and AI portfolios that includes companies like Paro, Krisp, and SupportLogic which acquired Emtropy Labs which was founded by great former guest Harish Batlapenamurthy. In full disclosure, Sierra and I are both investors in ArmorCode.Listen and learn...

1. Why the most successful venture investors were previously entrepreneurs
2. Tim's thesis for investing in gen AI customer journey company Simulate
3. How Tim identifies "gen AI whitewashing" when hearing pitches
4. Why gen AI is more than just another platform shift
5. How gen AI startups can beat Big Tech incumbents
6. Why all companies are ultimately "financial products"
7. Sierra's primary data from CIOs: "...they're spending money on use cases that unlock employee productivity"
8. What Tim means by "build horizontally but execute vertically"
9. Which jobs AI will eliminate vs. augment
10. Tim's "one that got away" pitch from his early days at Sierra

References in this episode...

• According to majority-of-americans-have-strong-reservations-about-ai-emergence-cnbc-survey-shows.html">CNBC, 69% of U.S. adults are uncomfortable with AI that can mimic human thinking
• Ashu Garg from Foundation Capital on AI and the Future of Work
• Rory O'Driscoll from Scale Venture Partners on AI and the Future of Work
• Sierra Ventures

We've had interesting conversations about remote-first work with leaders like Jordan Husney, Parabol CEO, and Darren Murph who at the time was the global head of remote work at GitLab (thank you Darren for the intro to Adam). Today's guest has been building a platform to make distributed teams productive since long before it was fashionable. Adam Nathan founded Almanac in January of 2019 to challenge incumbents like Microsoft Office and Google's GSuite. 

Since then, he and the team have enabled organizations like Cisco, Credit Karma, and ByteDance to collaborate in shared workspaces.

Adam has raised more than $40M to date across two rounds from a legendary group of investors that includes Floodgate, Tiger Global, and General Catalyst. Prior to Almanac, Adam did his undergrad at Duke and he received his MBA from Harvard. He's also an active volunteer for The Salvation Army.

Listen and learn...

1. How being a product manager at Apple and Lyft inspired Adam to start a company to avoid wasting time at work
2. What's unique about remote-first work
3. Why remote teams need structure and transparency to be productive
4. How to eliminate time wasted in meetings without losing opportunities to build trusted relationships
5. How to charge for new LLM features in SaaS products
6. Why we tolerate LLM hallucinations
7. Where there's a gap in the market for a better collaboration experience
8. What Adam has learned from his entrepreneurial journey 

References in this episode...

• Jordan Husney from Parabol  on AI and the Future of Work
• Darren Murph from GitLab on AI and the Future of Work
• Why we need to shut down AI development to prevent AGI
• Almanac.io

Durga Mulladi is the SVP & GM for Technology Planning & Edge Solutions at Qualcomm Technologies, Inc., the iconic company best known for enabling cell phones via its CDMA technology and chipsets that were first demonstrated in 1985. Durga has been an integral part of Qualcomm's growth having spent nearly 26 years there in various technology leadership roles.

He holds 578 patents, is a senior member of IEEE, received his PhD in '98 from UCLA, and was awarded Qualcomm's IP excellence award. Durga's list of accolades and accomplishments goes on for days. We're all fortunate to learn from a wireless pioneer and true tech legend.Listen and learn...

1. Durga's insights from more than 25 years pioneering wireless technology
2. An insider's view of Qualcomm's formula for success
3. How networks and chips enabled the birth of the smartphone
4. Qualcomm's AI roadmap
5. How soon we can expect LLMs running locally on phones
6. How AI takes advantage of the unique capabilities of 5G networks
7. How to figure out what transactions happen on the device vs. in the cloud
8. How LLM fine-tuning may soon happen on the edge of the network or on the device
9. What size LLMs can be run locally while managing power consumption
10. How to improve consumer trust in LLMs

References in this episode...

• JP Vasseur from Cisco on AI and the Future of Work
• Rene Steenvorden from Randstad on AI and the Future of Work
• to-know-chatgpt-code-interpreter.html">How OpenAI's code interpreter is disrupting the field of Data Science

In 2020 when today's guest founded her company the transformer architecture was relatively new and OpenAI was a science experiment funded by Elon Musk to ensure that AGI benefits all humanity. She and her team commercialized an early version of a co-pilot for writing content long before we appreciated the value of next-word prediction.

Since then, May Habib and the team have raised $21M from an exceptional group of investors including Insight Partners and Gradient Ventures. Today, Writer helps company authors comply with style and brand guidelines and also ensure grammatical accuracy. It's used by an amazing list or organizations including Spotify, Intuit, and Uber.

Prior to Writer, May co-founded Qordoba and was a Global Shaper for the World Economic Forum after graduating from Harvard with a BA in Economics.

Listen and learn...

1. How May got her start in NLP
2. What enterprise leaders don't understand about the current state of generative AI
3. How to speak to your data using LLMs 
4. Why Writer uses graph databases instead of vector databases for generative AI
5. How Writer mitigates the impact of bias, copyright infringement, and halluciations when using LLMs
6. How AI is being used to replace tasks people hate... without eliminating jobs
7. How AI helps users with neurodiversity issues like ADHD
8. How May navigated a tough company pivot

References in this episode...

• Mona Akmal, Falkon CEO, on AI and the Future of Work
• Alex Capecelatro, Josh.ai CEO, on AI and the Future of Work
• Making the web more accessible with AI for those with disabilities

Today's guest created one of the largest communities for conversational AI and generative AI enthusiasts. Pete Erickson is the founder of Modev which hosts the popular VOICE & AI conference and also others including the GovAI Summit. Pete started the company back in 2009 and has since produced over 150 events across 89 countries that have connected more than 125,000 people. Pete and the team have created communities for tech companies like Samsung and Amazon. Today, we get a glimpse into the mind of a great entrepreneur who is focused on making AI education accessible to everyone.Listen and learn...

1. How Modev went from a few people in a pizza shop... to a conversational AI event with more than  1,000 attendees
2. How Modev trained developers to build Alexa skills... in 2009
3. How new AI regulation is impacting the generative AI developer community
4. How Pete would regulate generative AI
5. About Sam Altman's request to Congress for OpenAI to be regulated
6. Should we expect AI vendors to regulate themselves?
7. What we can learn from GDPR in Europe about forthcoming AI regulation
8. How AI will transform the entertainment industry
9. Which jobs will be replaced by AI... and which ones are future-proof
10. What big news Pete will be announcing at the Voice & AI conference

References in this episode...

• The Voice & AI conference
• ai-could-raise-global-gdp-by-7-percent.html">How Goldman Sachs says AI will increase global GDP
• Bradley Metrock, CEO of Project Voice, on AI and the Future of Work
• Daniel Davila, movie producer and Hollywood consultant, on AI and the Future of Work

Entrepreneurs wonder what it’s like to be a VC. And VCs without an operating background often don’t understand the grit required to turn an idea into a successful business. The best investors have been successful operators first.

Today’s guest is one of those. Nick Adams founded Differential Ventures in 2017 to invest in B2B, data-first seed-stage companies. Since then, Nick and the team have invested in an impressive group of companies including Private AI, Ocrolus, and Agnostiq.

Before Differential, Nick helped grow companies like OPower and RAGE Frameworks in sales, marketing, and product leadership roles. Today we get to learn about how to innovate and grow a startup when the product is a venture fund.

Listen and learn...

1. How being an investor and entrepreneur are similar
2. The most outrageous pitch Nick has heard... and how it involved porn
3. How being a baseball player trained Nick to be a venture capitalist
4. Nick's advice for what to do after closing a big sales deal
5. Where there are opportunities for generative AI entrepreneurs to get funded
6. How AI is being used to design circuit boards
7. Nick's most recent investment... and what made him decide to write the check
8. What Nick is telling Congress we need to do to regulate AI

References in this episode...

• Why generative AI is desperately in need of regulation
• Metafold, new Differential investment
• Dan Grunfeld from Lightspeed on AI and the Future of Work

Vijay Tella is an enterprise software legend having founded unicorn and Cloud100 company Workato nearly a decade ago after an amazing run as the founding SVP of Engineering at TIBCO and CEO of Qik which was acquired by Skype.

Vijay is a visionary leader who has raised more than $400M and built a team of nearly 1,000 employees. Workato is a leader in the fast-growing enterprise automation space and the company's customer list reads like the Wall Street Journal including organizations like Adobe, Atlassian, Coca-Cola, and Walmart to name a few.

Vijay's latest achievement is his book The New Automation Mindset - launching today on this podcast - in which he and his co-authors put the current generative AI euphoria into historical context and provide timely insights and case studies. 

Thanks to great former guest Carter Busse, Workato CIO, for the intro to Vijay.

Listen and learn...

1. How Vijay got his start as a "digital plumber" at TIBCO and Oracle
2. What Vijay learned about enterprise software delivering a consumer app at Qik
3. How modern tools democratize access to automating work
4. Vijay's advice to leaders about what to automate first
5. Why "replacing people with AI is the wrong approach"
6. How Workato is incorporating generative AI into its product
7. How AI is required to get the full benefit of automation
8. What jobs will replace those eliminated by automation

References in this episode...

• The New Automation Mindset by Vijay Tella
• Carter Busse on AI and the Future of Work
• Guru Banavar from Viome on AI and the Future of Work
• The Khanmigo AI tutor

Christopher Penn writes one of the few newsletters I read weekly. I have no idea how I ended up on his mailing list but I’ll never opt out despite the rainbow “Unsubscribe here” buttons he prominently displays.

Christopher provides well-researched, thought-provoking commentary on all topics related to generative AI. Like recent guests Pradeep Menon and Ken Wenger Christopher doesn’t settle for soundbite-level commentary and he often shares unpopular opinions backed up with data.

Christopher is the Co-Founder and Chief Data Scientist at TrustInsights.ai. He’s a six-time IBM Champion in IBM Data and AI, a Brand24 Top 100 Digital Marketer, an Onalytica Top 100 AI in Marketing influencer, and co-host of the award-winning Marketing Over Coffee marketing podcast. He is also the author of two dozen marketing books. His list of accolades and accomplishments goes on for days.Listen and learn...

1. The number one question Christopher asks data-driven marketers
2. What has surprised Christopher most about the capabilities of LLMs
3. Why the letter to pause AI was "dumb"
4. The right way to remove bias and hate speech from LLMs
5. Open source vs. closed source AI... and how it's related to making pizza
6. Are we ready for AI vendors to censor content?
7. Christopher's predictions for how all enterprise software will incorporate generative AI
8. Why Christopher continues to hone his bow and arrow skills

References in this episode...

• Pradeep Menon on AI and the Future of Work
• Ken Wenger on AI and the Future of Work
• Tiernan Ray on AI and the Future of Work
• Christopher's (entertaining and informative!) newsletter
• DreamGPT... to glorify LLM hallucinations
• The bots aren't sentient!

About 54 million Americans and 936 million patients globally suffer from sleep apnea and 80% of cases go undiagnosed. Today’s guest is fixing that problem.

Chris Fernandez co-founded EnsoData in June 2015 to use AI to make sleep studies more efficient, cost effective, and accurate.

Since then, he and the team have raised more than $30M from an exceptional group of investors including Zetta Venture Partners, M25 Ventures, and Inspire Medical Systems.

Chris received his bachelors and masters degrees from the University of Wisconsin-Madison in Biomedical and Medical Engineering. He also wrote one of the most thoughtful perspectives on the entrepreneurial journey when he handed over the reigns to new CEO Justin Mortara last November. At 8,200 words, it may also be one of the longest.

Listen and learn...

1. What led Chris to care about solving sleep problems
2. How EnsoData overcame being "a solution in search of a problem"
3. How AI and machine learning can be applied to sleep apnea
4. How being incubated by Y Combinator helped launch EnsoData
5. How to use brainwaves to train AI models to diagnose sleep issues
6. When we'll get "smart rooms" that adjust the environment to optimize for healthy sleep
7. How Chris and the team control for the impact of AI bias
8. How to improve the quality of your sleep... from an expert
9. What led Chris to replace himself as CEO

References in this episode...

• Gordon Wilson, Rain Neuromorphics CEO, on AI and the Future of Work
• Why We Sleep by Matt Walker
• Stanford Professor Dr. William Dement and the origins of sleep science

We’ve had interesting recent discussions about AI and the law with great guests like Robert Plotkin. And we’ve had many interesting conversations about AI with CIO legends like Mark Settle from Okta and Carter Busse from Workato to name a few. In over 200 episodes we haven’t yet discussed how to deliver IT service to the legal industry.

Jim McKenna has been delivering technology to attorneys and coaching others who do the same for more than two decades. In his current role at perennial Silicon Valley top law firm Fenwick & West, Jim supports an organization of more than 1,000 employees as CIO. He oversees teams that manage IT and security and is first and foremost a thought leader for the business. Prior to Fenwick, Jim held similar roles at Morrison and Forester. He is also a member of the Board of Directors of the International Legal Technology Association.

Thanks to Xavier, unsung hero and Fenwick IT specialist, for helping with A/V issues.

Listen and learn...

1. What's unique about delivering IT and security service to lawyers
2. How the legal industry shifted to work from home during the pandemic
3. What's ahead for LegalTech
4. Where there are opportunities for AI to predict future employee needs
5. How Jim keeps up with security and compliance requirements... while innovating
6. Jim's leadership advice: "Prepare in advance so when the tough occurs you're not afraid!"

References in this episode...

• Robert Plotkin on AI and the Future of Work
• Mark Settle on AI and the Future of Work
• Carter Busse on AI and the Future of Work
• How generative AI is being used to analyze patterns in DNA sequences

Today’s guest has had a front row seat for every technology platform shift for the past 20+ years. More important, he has played an important role in enabling several of them.

Kit Colbert joined tech stalwart VMware in September 2003 and currently serves as senior vice president and chief technology officer. He is responsible for ensuring VMware’s long term technology leadership through research and innovation programs. Kit manages the VMware Engineering Services team, advanced R&D initiatives, the Design/UX team and the company’s ESG commitments.

Kit was previously VMware’s Cloud CTO, General Manager of VMware’s Cloud-Native Apps business, CTO for VMware’s End-User Computing Business, and the lead architect for the vRealize Operations Suite. 

Kit is a recognized thought-leader on application modernization and multi-cloud trends and a frequent speaker. He holds a bachelor’s of science in computer science from Brown University.Listen and learn...

1. How a Silicon Valley stalwart like VMware innovates from the inside
2. How VMware's founder-led culture continues to influence the company today
3. How VMware reinvented itself beyond desktop virtualization
4. Kit's recipe for innovation
5. Why crypto and AI hype are similar
6. Kit's perspective on how to regulate AI
7. VMware's generative AI strategy

References in this episode...

• Andi Mann from Sageable and Splunk on AI and the Future of Work
• Diane Greene and the history of VMware
• Kit's team's blog

Ron Bodkin is a self-described “serial entrepreneur focused on beneficial uses of AI”. Ron founded ChainML in April 2022 to make it easier to integrate AI models into applications. The AI we know today is immature in so many ways and many of them relate to how crude the tooling is for traditional developers building AI-first features. The ChainML protocol is a cost-efficient, decentralized network built for compute-intensive applications running on blockchain technology. Prior to founding ChainML Ron had a distinguished entrepreneurial career having founded Think Big Analytics before it was eventually acquired by Teradata after which he spent three years in applied AI at Google. Ron is also an active investor and advisor and has degrees in Computer Science from McGill and MIT.Listen and learn...

1. What led Ron to focus on how AI can have a positive impact on the world
2. Why Hinton's right when he says "we've invented a superior form of learning"
3. Where the current toolstack for building LLM apps is incredibly immature
4. How to control the cost and performance of LLM apps
5. Why human brains are inefficient
6. Why the "effective cost of computing" is being reduced by 50% every year
7. How we may get to AGI within 20 years
8. Why proprietary datasets and commercial issues will slow down AI innovation
9. The right way to regulate AI

References in this episode...

• Meredith Broussard, professor and author, on AI and the Future of Work
• Attorney relies on court cases made up by ChatGPT
• The Microsoft Sparks of AGI paper

Trent Fitz is the Chief Product Officer at Zenoss after having spent two decades in product and marketing leadership roles at companies like Trustwave and SailPoint.Trent owns product strategy and marketing at one of the pioneers in the space. Zenoss was founded in 2005 and has continued to reinvent itself. With the advent of generative AI, it’s more relevant than ever.We’ve explored the topics of service assurance and monitoring in the past with great guests like Colin Fletcher who coined the term AIOps while at Gartner and Gareth Rushgrove from Snyk who publishes the popular DevOps Weekly newsletter.

The field of monitoring is evolving rapidly as new architecture patterns emerge and the data exhaust they generate continues to increase. 

Listen and learn...

1. Trent's history lesson in system monitoring
2. The role of AI in monitoring and operations
3. Trent's perspective on the evolution of monitoring tool sprawl
4. What is AIOps vs. observability, monitoring, or event management
5. How service-centric monitoring is essential for dynamic apps based on microservices
6. The difference between generation one and two AIOps
7. Where are manual rules insufficient and real AI is needed to monitor apps
8. How LLMs are being used to improve observability
9. Why Big Cloud won't own monitoring of cloud-native apps
10. Will there be a time when AI will replace DevOps engineers?

References in this episode...

• Colin Fletcher from Gartner on AI and the Future of Work
• Gareth Rushgrove from Snyk on AI and the Future of Work
• Charity Majors on AI and the Future of Work

Today's guest is one of the pioneers in generative AI having spent nine years at Google Research building teams that developed breakthrough technologies that led to innovations like the transformer architecture behind ChatGPT.Jad Tarifi co-founded Integral AI in 2021 after a distinguished career in AI roles as a researcher and leader. He received his PhD in Computer Science and AI from the University of Florida and did his undergrad at the University of Waterloo.

Thanks to great former guest and friend of the podcast Hina Dixit from Samsung NEXT for the intro to Jad.

Listen and learn: 

1. Can machines learn common sense? Do humans have common sense? 
2. Why Integral AI is providing a “base model for the world” 
3. Can machines ever learn as quickly as humans? 
4. How to improve the efficiency of LLMs with better algorithms 
5. Why the current transformer architecture is poorly designed for next word prediction 
6. How to use AI and robotics to create “magic wands” and “crystal balls” 
7. How to use AI to do “science at scale” 
8. What are the ethical implications of bots that can change the human life span 
9. How AGI is related to objective morality 
10. Jad’s four tenets of a new definition of “freedom” 

References in this episode… 

• Integral.ai 
• Blake Lemoine and the “sentience” debate
• Podcastle, generative AI for podcasts (a technology nobody needs)

Today’s guest is one of the original AI-first entrepreneurs. SambaNova paved the way for generations of other companies including today’s generative AI cohort. Rodrigo Liang, CEO, and his team have raised more than a billion dollars from a legendary group of investors including Temasek, BlackRock, GV, and Walden International.

The original vision for SambaNova’s chip architecture and software products came from work his co-founders did at Stanford’s famous AI Lab. Today, SambaNova has embraced generative AI and is again leading the industry. Before founding SambaNova, Rodrigo held senior leadership roles at Oracle and Sun after having received his masters and bachelors degrees in Electrical Engineering from Stanford.

Listen and learn… 

1. Why AI will be bigger than the internet 
2. How SambaNova migrated from designing AI chip architectures to software 
3. How to build your own LLM like ChatGPT 
4. Where there are opportunities for companies beyond NVIDIA in the AI chip space 
5. What will lead to the “trough of disillusionment” for AI 
6. What are adjacent opportunities for AI outside chat that are at the early stages of maturity 
7. How every knowledge worker will soon benefit from an AI personal assistant 
8. How to address the problem of popular LLMs being trained mostly on English content
9. Why we’re in the “Linux moment for AI” 
10. What contributes to the cost and complexity of training new LLMs 
11. What is fine-tuning and how does it work 

References in this episode… 

• Sam Altman calls for global cooperation to regulate AI
• The SambaNova technical blog 
• The SambaNova partnership with Together.xyz to train BLOOMChat 
• Christopher Nguyen, Aitomatic CEO, on AI and the Future of Work 

We’ve interviewed some legendary CIOs including Mark Settle from Okta (a repeat guest), Reza Nazeman from SAP Concur, and, more recently, Carter Busse from Workato.

We’re joined by another unicorn CIO today, Karl Mosgofian. Karl has helped grow Gainsight to more than $200M ARR and 1,200 employees. He has been leading the IT organization for nearly six years after having spent time at Harmonic, Apple, and Cadence Design.

Thanks to friend of the podcast Carter Busse for the intro to Karl.Listen and learn...

1. How Karl's role has changed since he joined Gainsight as a startup six years ago
2. Why it's hard for CIOs to "just keep the lights on"
3. How Karl navigates the duel role of enabling the business to innovate with technology while making sure teams stay focused on solving business problems
4. How Karl formulated the Gainsight employee ChatGPT policy
5. Why ChatGPT won't replace the help desk
6. Karl's advice to vendors embedding AI in their products
7. How Karl partners with his CISO and legal team to establish policies for LLM usage
8. How Gainsight is using AI internally to improve productivity
9. All about the quirky culture at Gainsight

References in this episode...

• Mark Settle on AI and the Future of Work
• Carter Busse on AI and the Future of Work
• Reza Nazeman on AI and the Future of Work
• Legendary Gainsight videos on YouTube

No field is being upended as much as the legal profession. We’re all confused about how content generated by AI will be protected under the law and many lawyers are also asking how relevant they’ll be in a world where large language models can pass the bar and do legal research.

Robert Plotkin is a luminary in the software patent space having been in the field for 25 years and having been involved in important IP cases related to everything from AI to quantum computing to autonomous vehicles and speech recognition.

Robert also published the book Genie in the Machine back in 2009 which amazingly foreshadowed the legal implications of AI on IP. Robert has lectured at the Boston University School of Law and received his undergrad in Computer Science and Engineering from MIT.

Listen and learn...

1. How we should regulate LLMs... from an expert
2. What entrepreneurs most often don't understand about IP law
3. Who has the rights to the inputs to LLMs?
4. Can work derived from LLMs be patented?
5. Is AI-generated work subject to copyright laws?
6. What surprised Bill Gates when he saw GPT-4
7. Is there an AI winter up ahead?

References in this episode...

• Robert's personal site
• Harvey raises $5M to be the AI co-pilot for lawyers
• Andy Clark's Natural-Born Cyborgs
• Bob Rogers, AI pioneer, on AI and the Future of Work
• The Blueshift IP whitepaper about how AI is automating the inventive process

Today’s guest is the author of a popular Medium blog where he has recently been dissecting generative AI for technologists. I read his introduction to the transformer architecture and immediately realized our audience needs to meet him. A bit like great recent guest Ken Wenger, Pradeep makes complicated technology accessible. 

By day, Pradeep Menon is a CTO at Microsoft's digital natives division in APAC. He has had one of the best ground floor views of generative AI since Microsoft first invested in OpenAI in 2019 and then again in March of this year.

Pradeep was previously in similar roles at Alibaba and IBM. He speaks frequently on topics related to emerging tech, data, and AI to global audiences and is a published author.

Listen and learn...

1. What surprises Pradeep most about the capabilities of LLMs 
2. What most people don't understand about how LLMs like GPT are trained 
3. The difference between prompting and fine-tuning 
4. Why ChatGPT performs so well as a coding co-pilot 
5. How RLHF works 
6. How Bing uses grounding to mitigate the impact of LLM hallucinations 
7. How Pradeep uses ChatGPT to improve his own productivity 
8. How we should regulate AI 
9. What new careers AI is creating 

References in this episode...

• Ken Wenger on AI and the Future of Work 
• Pradeep's book Data Lakehouse in Action
• id.com/speaking-portrait/">D-ID speaking avatars

We often discuss the technology that is automating the future of work. We perhaps don’t spend enough time talking about the human element - what it’s like being an employee whose career may be at risk or whose employer may not share her values. The future of work is about employers embracing the humanness of every employee and creating safe places. 

Mark McCrindle is a best-selling author, futurist, demographer, and popular TEDx speaker who is regarded as one of Australia’s foremost social researchers. He works with senior leaders to help them devise strategies for making their products and services future-proof. He’s also the host of The Future Report, a podcast featuring the themes of his social research.Listen and learn...

1. How work culture directly impacts employee productivity
2. How to measure the quality of employee experiences
3. How the mining industry attracts and retains workers... and how AI may replace traditional roles
4. Should humans feel threatened by AI?
5. Mark's advice to young leaders
6. Why Mark says "we're made for work"... but that doesn't necessarily require an exchange of time for money
7. How human relationships with machines will always be different than human relationships with each other
8. Why the culture in Sydney is uniquely favorable for entrepreneurs

References in this episode...

• Mark's social research
• mccrindle publications
• AI's impact on humanity with Gary F. Bengier
• Bryan Talebi, Ahura AI CEO, on AI and the Future of Work

What does it mean to be human when your colleague's a bot? Can AI ever truly understand us? This week, we're thrilled to welcome Gary F Bengier, eBay's first CFO and author of the award-winning novel, Unfettered Journey, as we dive into the future of work and the role of AI. Gary's background in Silicon Valley and his understanding of AI and technology make him the perfect guest to shed light on the ethical implications of AI, the potential impact of large language models on business, and the crucial differences between symbolic software and large language models.As we unpack the World Economic Forum's prediction that AI will generate 97 million new jobs while eliminating 85 million in the next three years, Gary and I contemplate the implications of machines and humans working together. We discuss the possibility that robots could eventually build robot factories, detaching the output of the economic system from labor hours, and explore the question of sentience in the age of advanced technology. Join us for an important conversation and peer into the mind of one of the great philosophers and technologists of our time.Oh, and learn what Gary says is a better definition for the acronym "LLM" :).References in this episode:

• Tiernan Ray on AI and the Future of Work
• Wow... ChatGPT is very thirsty!
• The Santa Fe Institute
• Gary's book Unfettered Journey

The current Hollywood writers strike is the highest profile example of shifting dynamics in the entertainment industry. Studios are spending less to produce more content. Fees paid to writers have plummeted. Generative AI is only accelerating the trend. This has profound implications for the future of storytelling.

Today’s guest is an expert in the entertainment industry having founded Divisadero Pictures in 2011 to advise entertainment companies from Disney to Comcast to Microsoft on strategy and finance topics. Daniel Davila received his MFA from USC and his MBA from Stanford. 

For historical perspective, today is only the second episode in more than 190 where we’ve discussed AI and the future of the work in the entertainment industry. For long-time listeners the last time was episode 87 back in April 21 with Michael Solomon and Rishon Blumberg, authors of Game Changer: How to be 10x in the Talent Economy, who  managed Bruce Springsteen and John Mayer in a previous life.

Thank you to friend of the podcast Matthew Perez for the introduction to Daniel.

Listen and learn...

1. The history of media consumption patterns
2. The economics of the entertainment industry
3. How AI is changing the entertainment industry
4. How Daniel used generative AI tools to write a 70-page movie script
5. Daniel's pitch to Francis Ford Coppola about the role of AI in movie-making
6. The impact of streaming on media production and consumption
7. The bias inherent in text to image tools like Midjourney

References in this episode...

• Michael and Rishon, Bruce Springsteen's former managers, on AI and the Future of Work
• Divisadero Pictures
• The Hollywood writers strike

Guru Banavar is the founding CTO of Viome where he helped raise $150M from a list of top-tier investors including Khosla Ventures and Bold Capital Group. Viome offers insights into health and disease using host and microbiome gene expression. Guru led the development of a first-of-a-kind saliva-based early detection system for oral and throat cancers which won the FDA’s designation as a breakthrough device.

Prior to Viome, Guru was a global VP & Chief Science Officer at IBM and the founding VP of the Watson AI Research team.

Guru has received many awards including a Leadership in Technology Management Award and a National Innovation Award from the President of India. He has published extensively and holds more than 35 US patents. His work has been featured in media outlets including the New York Times, the Economist, the Wall Street Journal, BBC, and NPR.

Listen and learn… 

1. Why our healthspan is more important than our lifespan 
2. How DNA to RNA transcription determines your health state 
3. How to sequence your mRNA to understand how to optimize your diet and predict disease risk 
4. What AI techniques can be used to develop personalized treatments 
5. How to use data that varies across patients to make automated decisions for all patients 
6. How Guru thinks about false positive prescriptions as a scientist when health and safety are at stake 
7. Where the FDA is regulating how AI is used to make healthcare recommendations 
8. Why it’s impossible to know the best diet for you without first understanding the composition of your microbiome 
9. How to use biomarkers to turn your biological fingerprint into a data problem 
10. Guru’s perspective on the ethical and philosophical implications of extending the healthspan 
11. How digital twins will help perfect the ability to engineer biology 

References in this episode… 

• What it means to practice responsible AI
• The KEGG ontology of biological pathways 
• The Viome blog 
• Dr. Shiv Rao, CEO of Abridge, on AI and the Future of Work

Today’s guests are using machine learning to turn real world data from past interactions into insights. Dr. Hyde is the co-founder and CEO of Atropos Health which has commercialized the insights exchange for healthcare. Dr. Hyde raised a $14M series in August 2022 from an exceptional group of investors including Breyer Capital and Emerson Capital. Dr. Hyde is joined by an early user of Atropos, Dr. John Halamka, President of the Mayo Clinic Platform. Dr. Halamka has been developing and implementing healthcare information strategy and policy for more than 25 years. He specializes in artificial intelligence, the adoption of electronic health records and the secure sharing of healthcare data for care coordination, population health, and quality improvement. He was elected to the National Academy of Medicine in 2020.

For AI and the Future of Work trivia buffs this is one of only three episodes we’ve recorded with multiple guests. The last one with Tooso founders Ciro Greco and Jacopo Tagliabue was one of our most memorable.

Listen and learn...

1. Why ChatGPT shouldn't be used for medical diagnoses
2. How Atropos uses healthcare data from the Mayo Clinic Platform combined with AI to assist caregivers
3. How to use AI to automate the research that can otherwise takes weeks or months
4. How the lack of access to data-driven recommendations leads to dangerous patient outcomes
5. Who is responsible when AI makes a bad decision that adversely impacts a patient
6. How to use NLP to remove PII to make it usable by AI (and certify data hygiene)
7. The challenges of managing patient data at scale in a way that complies with HIPAA regulations

References in this episode...

• ChatGPT's phenomenal adoption rate... by the numbers
• Ciro and Jacopo from Tooso (acquired by Coveo) on AI and the Future of Work
• Paddy Padmanabhan on AI and the Future of Work
• Dipanwita Das, Sorcero CEO, on AI and the Future of Work
• The Mayo Clinic Platform
• Atropos Health

Dr. Shiv Rao is a cardiologist, teacher, former corporate VC, and the CEO of an exciting company that is changing how doctors help patients. Dr. Rao started Abridge in March 2018 to solve one of the biggest problems in healthcare. He has since raised $27M most recently in a $12.5M series A extension last August from leading investors including Bessemer, Union Square, Wittington Ventures, and legendary AI pioneer Yoshua Bengio.

Today we explore what happens when AI automates the error-prone task of doctors taking notes during patient visits. It’s easy to imagine a world where quality of ilife improves because doctors are present, focused on patient outcomes, and able to develop more genuine, human relationships while AI automates everything else.

Listen and learn… 

1. How much of a doctor’s time is spent not focused on patient care 
2. How AI can replace “pajama time” for doctors… and reduce burnout 
3. Why doctors require a 27-hour work day to deliver the quality of care patients expect 
4. How to use generative AI to assist doctors to capture better notes 
5. Who is responsible when AI makes mistakes that lead to incorrect diagnoses for patients 
6. Why AI won’t replace doctors… but doctors using AI may replace doctors not using it 
7. How Abridge reduces the risk of generative AI hallucinations 
8. How a design thinking lecture changed Dr. Rao’s life 

References in this episode… 

• Paddy Padmabhan discusses the future of healthcare on AI and the Future of Work 
• The Abridge homepage 
• The open letter from Musk, Wozniak, and others to “slow down” the pace of AI development

Guillermo Corea is the Managing Director of the SHRM Workplace Innovation Lab and Venture Capital initiatives. He joined SHRM in 2015. He and his team are focused on finding and cultivating technologies that will impact the future of work. Guillermo’s team organizes the SHRM Better Workplaces Challenge Cup and Workplace Tech Accelerator plus they lead the organization’s impact investing program. Guillermo is a vocal leader in the HRTech community.  

This was a fun one because we got to record in person at SHRMTech 2023 in San Francisco. Only our fifth live recording in more than 190 episodes!

Listen and learn...

1. How HR teams should drive workplace innovation 
2. Which Shark Tank shark is judging the Better Workplaces Challenge Cup
3. How SHRM Labs connects tech entrepreneurs with HR leaders 
4. Why the CHRO is the most strategic exec in the C-suite 
5. How the pandemic and an aging employee population are creating opportunities for HRTech 
6. The technology Guillermo says will change work most in the next decade 
7. How to confront the problem of biased algorithms making HR decisions 
8. Why the HR blockchain will replace background check vendors 
9. The HRTech company Guillermo is ready to fund! 

References in this episode...

• Reza Nazeman, former CIO of SAP Concur, on AI and the Future of Work
• Kamal Ahluwalia, Eightfold President, on AI and the Future of Work
• Jason Corsello, VA at Acadia Ventures, on AI and the Future of Work
• SHRM Labs

Daniel Marcous comes to fintech from an unconventional background. Before co-founding April he was the CTO for the Waze product at Google, the social traffic app originally called FreeMap Israel that was acquired by Google in 2013 for $1.3B. Daniel started his career as a data scientist in the Israeli Defense Force and actively gives back to the Israeli Data Science community through involvement with DataHack, DataLearn, and KaggleIL.Listen and learn...

1. What Daniel learned at Google and Waze about scaling AI
2. Why an Israeli data scientist left Google to start a company automating tax filing for Americans
3. Why doing taxes is like finding the best route on a map
4. Why continuous tax planning is the future of personal finance
5. How to manage consumer data responsibly... and still use it to train AI models
6. Why the U.S. tax code is so complicated
7. Why ChatGPT will never do your taxes
8. When AI will replace CPAs
9. Daniel's favorite cocktail

References in this episode...

• Why you shouldn't trust search results from LLMs
• The April blog
• Daniel's gallery of home-made cocktails
• Arvind Jain, Glean CEO, on AI and the Future of Work

Artem Koren, co-founder and Chief Product Officer at Sembly AI, started the company in January 2019 to bring the power of AI to online meetings. Artem and his team developed an app that listens in on virtual meetings and does all the note-taking for you including recommending action items and suggesting the most important topics. These are hard AI problems to solve and Sembly’s success is an indication they’re off to a great start.

Before Sembly, Artem was an executive and co-founder at companies including Neusana and Visual Trading Systems and he spent time as a manager in big company land at Ernst & Young.

Listen and learn...

1. Why Artem and his co-founder decided to fix the problem of broken meetings 
2. Why the evolution of online meetings… is like the evolution of airplanes 
3. Why we’ll soon send AI agents to attend meetings on our behalf 
4. When meetings are required… and how to make them more efficient 
5. How neural nets are solving traditional voice transcription problems related to accents and background noise 
6. How to solve the problem of automatically determining who said what in a conversation 
7. How Sembly uses generative AI to summarize meetings 
8. What are the risks of having AI decide what tasks to assign to meeting participants 
9. How to prevent sensitive information from being passed to large language models as training data 

References in this episode... 

• Safety and ethics are being compromised in the rush to get new generative AI products to market
• Krish Ramineni from Fireflies on AI and the Future of Work
• Rich White from Fathom on AI and the Future of Work
• Sembly AI

Today’s guest is one of the most recognized investors and thought leaders in the conversational AI community. Bradley Metrock is the CEO of Project Voice, author of the popular Substack newsletter This Week in Voice with more than 30,000 subscribers, and a General Partner at Project Voice Capital Partners. Congrats to Bradley and the team on their recent announcement of their new rolling fund. 

Bradley’s a proud citizen of the Volunteer State of Tennessee. Fair warning: you may be ready to move to Chattanooga after today’s conversation. Oh, and he’s also an ironman in the world of podcasting having just launched season eight of This Week in Voice, a podcast he launched in 2017. We’re on about episode 180 of this podcast going back to 2019 so I admire Bradley’s stamina.

Listen and learn… 

1. Where there’s opportunity for entrepreneurs to innovate in conversational AI 
2. How conversational AI is changing quick serve restaurants, contact centers, banking, and hospitality 
3. How Bradley evaluates new pitches at Project Voice Capital Partners 
4. How Bradley defines voice technology in his market map 
5. Is voice the new app… or perhaps the “original app” 
6. Why generative AI is so disruptive 
7. Should we be concerned about voice assistants like Siri and Alexa listening in on our conversations 
8. What jobs will AI create over the next decade 
9. Bradley sells the great state of Tennessee to entrepreneurs establishing roots outside a coastal state 

References in this episode... 

• Dr. Lance Eliot describes the risk of sharing your data with ChatGPT
• Applied Brain Research, a Project Voice Capital Partners investment 
• Bradley’s voice technology market map 
• The Blueprint for an AI Bill of Rights 
• Project Voice 2023 

Ken Wenger is the author of the forthcoming book Is the Algorithm Plotting Against Us?: A Layperson’s Guide to the Concepts, Math, and Pitfalls of AI. I’ve been reading it and it is excellent. Ken is a deep thinker and a great writer. He’s also the senior director of research and innovation at CoreAVI and chief technology officer at Squint AI. His work focuses on the intersection of artificial intelligence and determinism, enabling neural networks to execute in safety critical systems. Kenneth has co-authored two articles in the scholarly journal Machine Learning with Applications and several white papers for different publications, including Embedded Computing Design. He also holds several patents under CoreAVI’s auspices.Listen and learn...

1. How neural nets emulate the brain to make decisions
2. Why we have to be careful when using the term "intelligence" to describe "AI" systems
3. When Ken trusts machines to make decisions... and when he doesn't 
4. Why LLMs like ChatGPT "hallucinate"
5. How generative AI replicates human bias
6. Why Ken feels "if we haven't addressed ethical issues we're not ready to deploy AI solutions"
7. What AI explainability is and why it's important

References in this episode...

• Ken's book: "Is the Algorithm Plotting Against Us: A Layperson's Guide to AI"
• Krishna Gade, Fiddler CEO, on AI and the Future of Work
• CoreAVI
• Squint AI
• Surprising results from the Pew Research Center's survey about attitudes toward generative AI

Bob Rogers, AI pioneer, entrpreneur, and author, started Oii in 2019 to automate supply chain design. The company uses advanced modeling and AI to optimize supply chain planning and automate the configuration of complex networks. Bob started his career as a Harvard physicist using neural networks to measure activity near black holes in deep space. During his 35 year career Bob has been a trailblazer in using AI to solve complex problems. He’s also an Expert in Residence for AI at UCSF Smarter Health and was Chief Data Scientist in the Data Center Group at Intel as well as co-founder and Chief Scientist at Apixio, a Healthcare AI company. Additionally, he co-authored the books Artificial Neural Networks: Forecasting Time Series and “De-mystifying Big Data and Machine Learning for Healthcare“. Bob received his BA in physics at UC Berkeley and his PhD in physics at Harvard. Listen and learn...

1. How neural nets work... from a pioneer
2. What it was like to co-author a book with ChatGPT
3. What surprised Bob most when he tested the boundaries of ChatGPT
4. Why ChatGPT spews credible nonsense
5. The ethics of using generative AI to sell content derived from copyrighted materials
6. Why ChatGPT became an instant global phenomenon
7. How OpenAI trained ChatGPT "to be nice"
8. Is there another "AI winter" ahead?

References in this episode:

• The book Bob co-authored with ChatGPT
• Can AI be an author of a publication in a scientific journal?
• Bob's previous book: Demystifying AI for the enterprise
• Stanford's Dr. Fei-Fei Li in conversation with OpenAI CTO Mira Murati
• Futurists Peter Scott and David Wood on AI and the Future of Work
• Bob's company: Oii.ai

Cisco got its start in 1984 connecting computers at Stanford University to form the first local area network. Other than maybe Microsoft or Apple, it’s easy to argue Cisco has had more influence on the growth of the internet, and by extension, the modern world, than any other company. 15 years after Cisco started today’s guest was hired to begin what would become a legendary career. 

Nearly 25 years later JP Vasseur has changed the world again and again. In the process, he has been recognized as the #1 inventor at Cisco with 600 patents to his name. He has authored or co-authored 35 standards, published three books on internet technologies, and has been recognized as a Cisco Fellow, a prestigious title awarded to the top few most-distinguished technical leaders at the company. Today we learn from a living legend about the past, present, and future of technology.

Listen and learn...

1. How AI at Cisco has evolved in the past 12 years
2. Disruptive vs. incremental innovation
3. How predictive networks learn
4. The design principle JP used when designing the first predictive network
5. The challenges of predicting outages using unsupervised vs. supervised machine learning
6. JP's process for innovating like a startup within Cisco
7. Innovation in networking we can expect in the next decade
8. JP's best memory from the early days of Cisco

References in this episode:

• JP's blog
• Kevin Roose from the New York Times had a disturbing conversation with Microsoft's Bing
• Chambers Talks, the great podcast from former Cisco CEO John Chambers
• Yann LeCun on how babies learn
• Phil McKinney, former HP CTO, on AI and the Future of Work

Navindra Yadav is the co-founder and CEO of Theom, the cloud data security leader. He and the team recently raised a $16M series A from an impressive group of investors including Microsoft’s M12 venture fund and Ridge Ventures. Prior to Theom, Navindra was the founder and CEO at Tetration and prior to that he was a distinguished engineer at Cisco. Navindra’s work has received more than 182 patents.

For full disclosure, Dan is an investor in Theom. Thanks to Patty Hatter, great former guest, for introducing us to Navindra.Listen and learn... 

1. What CISOs least understand about the security of enterprise data 
2. Why CASBs (Cloud Access Security Brokers) are inherently vulnerable 
3. The hardest technical problem Theom has solved 
4. How to assign a “criticality score” to data 
5. How to use NLP (natural language processing) to detect PII (personally identifiable information) 
6. How to protect from unauthorized data access through social engineering 
7. Why data stores like Snowflake, Databricks, and Confluent don’t already monitor data inappropriately leaving their platforms? 
8. When consumers will be able to trust that data they provide SaaS vendors is secure. 
9. The security startup Navindra and Dan are ready to fund! 

References in this episode… 

• Navindra’s company: Theom.ai 
• Patty Hatter on AI and the Future of Work 
• lieu-ai-chatgpt-congress.html">Congressman Ted Lieu on the creation of an “FDA” equivalent to regulate AI

We often discuss the future of work for enterprise employees. What technology will they use, how will people and machines interact, and how teams will be organized when geography and language are no longer barriers. Few have spent more time in and around enterprise service management than today’s guest and few are better qualified to share insights about what’s ahead.

Andi Mann has been a technology leader in technology companies around the world since the 90s. He founded Sageable, the digital transformation advisory services practice, in 2015 and has also recently served in roles that include CTO for DevOps at Splunk and VP Products and Strategy at CA which is now part of Broadcom. Andi and I both did time at BMC Software in the early 2000s. Andi is the author of multiple books including The Innovative CIO, he’s a sought after speaker, and tech provocateur who is never shy about what’s wrong with IT and where the world of digital is headed.

Thanks to friend of the podcast Steve Kaplan for the intro to Andi.

Listen and learn… 

1. Why Andi summarizes his career this way: "I make computers do more work to allow people to do more creative things" 
2. The best use of enterprise AI Andi has seen 
3. How Andi helped an industrial transportation company save a billion dollars 
4. Why “less complex systems can’t understand more complex systems” 
5. Why the best use of AI is targeting “known knowns” by augmenting vs. replacing human intelligence 
6. How to overcome the lack of trust in AI 
7. Why AI won’t eliminate any jobs… and why it will create many new ones 
8. Skills to invest in today that will never be replaced by automation 

References in this episode... 

• Dr. Lance Eliot writes about ChatGPT dispensing therapy advice 
• Colin Fletcher, father of the term “AIOps”, on AI and the Future of Work 
• Andi’s book “The Innovative CIO" 
• Andi’s company Sageable 

Meredith Broussard is one of the most visible, vocal leaders in the emerging field of algorithmic accountability. Professor Broussard is a data scientist and Associate Professor at NYU whose research focuses on AI in investigative reporting and using data analysis for social good. Meredith is the author of Artificial Unintelligence: How Computers Misunderstand the World and the forthcoming More Than a Glitch: Confronting Race, Gender, and Ability Bias in Tech. 

Among other things, Professor Broussard was featured in the seminal documentary Coded Bias. Today's discussion is about one of the most important topics in our field and in this episode we explore it with someone whose name is on a shortlist of AI ethics pioneers. You’ve heard me say repeatedly coursework in AI ethics should be required for every student graduating with a technical degree. Here's why!Listen and learn...

1. How AI reveals bias encoded in society
2. Why it's important to always ask "what could go wrong" 
3. What is the new field of "algorithmic accountability reporting"
4. What the Blueprint for an AI Bill of Rights may mean for bad acting companies
5. What's the right role for the federal government in AI regulation
6. How to assign an "accountability score" to algorithms
7. The ethical issues related to AI we'll be discussing in a decade

References in this episode...

• More Than a Glitch, Professor Broussard's new book... and her "love letter" to an amazing group of women who are pioneers in the emerging field of algorithmic accountability
• Professor Broussard's personal website
• The racist soap dispenser
• Joy Buolamwini's Algorithmic Justice League
• Rumman Choudary, formerly head of the META team at Twitter
• Cathy O'Neil's ORCAA
• The ethical judgments built into generative AI models
• Google's "stochastic parrots" debacle
• The Agnes Irwin School outside Philadelphia

Arvind Jain, Glean CEO and Rubrik co-founder, started Glean in March 2019 to make it easier to find answers strewn across myriad SaaS apps. Prior to Glean, Arvind had an incredible run at data security company Rubrik which he co-founded in 2014. Prior to Rubrik Arvind was a distinguished engineer at Google. Glean became a unicorn last year having raised $100M in May from a list of iconic investors including Lightspeed, General Catalyst, Kleiner Perkins, and Sequoia.

Enterprise search is one of the best examples of a field that was in desperate need of disruption. In this episode, we meet one of the disruptors.Listen and learn...

1. Where there's a gap in traditional search technology including Google
2. How to retrieve the best answers across hundreds of SaaS apps
3. How to understand what users need even when they don't know the right way to ask for it
4. How to use LLMs like ChatGPT to improve search accuracy
5. How products like Alexa and Siri are teaching us to ask questions using natural language rather than searching with keywords
6. How to personalize enterprise search without improperly using user data
7. What is the future of knowledge management

References in this episode...

• The ethics of ChatGPT
• Seth Earley from Earley Information Science on AI and the Future of Work
• The Glean blog

Parul Saini has been a technology leader at tech-first companies like Zuora, Splunk, and Uber for more than a decade in roles with increasing responsibility. She has had a birdseye view of AI tech trends and the future of work. In her current role at Uber, her service portfolio includes contact center, employee productivity, and identity management applications.

Today, we learn from an expert how to manage enterprise apps that support thousands of employees for a rapidly growing global company.

Listen and learn...

1. Why "empathy" is the baseline for IT
2. How to hire and retain IT talent
3. How to navigate the dual challenges of being a technology leader and people manager simultaneously
4. How to use AI to increase the velocity of hiring decisions
5. Why great CIOs... are also great at sales and marketing
6. What Parul has learned from Shantanu Narayen, Adobe CEO, and Dara Khosrowshahi, Uber CEO
7. One thing only Uber insiders know
8. Parul's advice for aspiring female IT leaders

References in this episode...

• Mark Settle, seven-time CIO, on AI and the Future of Work
• How autonomous vehicles are changing global traffic patterns

Binny Gill started his career as a programmer after studying CS and Engineering at IIT Kanpur and later UIUC, University of Illinois Urbana-Champaign. He then had an impressive eight-year run as a technology leader at Nutanix, the hyper converged infrastructure company, eventually becoming its CTO for cloud services. In January 2021, Binny left Nutanix to start Kognitos based on a bold vision to make everyone a programmer. In this discussion, we learn about his journey and how generative AI just may change everything.

Thanks to Steve Kaplan for the intro to Binny.

Listen and learn:

1. Binny's inspiration for starting Kognitos: "...why should humans need to think like machines... when machines can now think like humans?"
2. What makes programming so hard.
3. Why the future of programming is using natural language to describe the features you want.
4. How computing interfaces restrict us from communicating like humans when programming.
5. Why Binny says "generative AI is the new electricity."
6. The most important leadership lesson Binny learned working alongside iconic leaders at IBM.

References in this episode:

• How Petals just became the BitTorrent of LLMs
• Phil McKinney, former HP CTO, on AI and the Future of Work
• The Kognitos blog

Today’s guest belongs on the Mt. Rushmore of amazing female leaders we've interviewed on this podcast. Daphne and I met in November while co-presenting at the HMG Strategy event in New York City. Daphne’s energy is infectious. Her passion for inspiring leaders was obvious on stage and even more obvious when we met afterward. Daphne’s new book Win When They Say You Won’t: Break Through Barriers and Keep Leveling Up Your Success became an instant best seller. Listen to this one and you’ll understand why.

Before becoming an author, Daphne started The Board Curators to help others prepare for serving as paid company directors. She serves on numerous boards including AMN Healthcare and Masonite International. Earlier in her career, Daphne was a serial CIO serving in IT leadership roles at companies including IBM, Johnson & Johnson, Pfizer, and GE Healthcare.Listen and learn...

1. Daphne's remarkable path from poor kid in rural Illinois to global CIO
2. How to overcome racial bias as a black female
3. The subtle ways bias infiltrates organizations
4. Where imposter syndrome originates... and how to conquer it
5. How to "version your life" to adopt a growth mindset
6. How to use Daphne's EDIT process to achieve your goals
7. Why DEI "won't be a thing any more" in a decade

References in today's episode...

• Daphne's book: Win When They Say You Won't
• Charlene Li on AI and the Future of Work
• Giselle Mota on AI and the Future of Work
• Kai Nunez on AI and the Future of Work
• Daphne's website
• Fun facts about AI adoption in 2023

This is one of my favorite episodes of the year. It’s our third annual long, strange trip into the mind of a Silicon Valley legend. Dave Kellogg is one of the best marketers, CEOs, tech provocateurs, and board whisperers around. He was an executive at iconic companies like SAP, MarkLogic, and Salesforce turned investor and board director who is now an executive in residence at Balderton Capital. In this episode, we discuss, well, just about everything that matters for the tech economy… startup growth metrics, generative AI, how to get funded in 2023, and of course our favorite jam band.

Listen and learn: 

1. What Dave got right… and not so right… in his 2022 predictions 
2. How startups can survive downturns 
3. How to fix the problems at Salesforce, Amazon, and Facebook 
4. What single theme will characterize 2023 in Silicon Valley 
5. What will happen to startups that raised massive rounds in 2021 
6. Why virtual companies won’t outperform companies built around hubs in tech centers 
7. What’s ahead for consumption-based pricing and PLG 
8. Why generative AI poses an existential threat to Google 

References in this episode: 

• Dave’s (excellent) blog 
• Peter Fishman, Mozart Data CEO, on AI and the Future of Work 
• Derek Steer, Mode  co-founder, on AI and the Future of Work
• How ChatGPT can detect Alzheimer's disease

Carter Busse has been leading IT organizations for more than two decades. He has been an IT leader at successful, high-growth organizations ranging from Salesforce to MobileIron to 8x8 to Cohesity Among his many accolades, he was recently named a 2022 ORBIE Bay Area CIO of the year and was also the first IT leader hired at Salesforce back in 2000. Carter understands the challenges of managing tech infrastructure for high-growth tech companies where there’s zero margin for error because everyone thinks they know tech better than you. CIOs are like plumbing: nobody appreciates them when everything’s working but they’re the first to get blamed when there’s a blockage.

He's now the CIO of rising star Workato, the integration automation platform that has raised more than $400M, was most recently valued at nearly $6B, and has about 1,000 employees in 13 offices around the world. 

Listen and learn...

1. What a CIO does.
2. Why CIOs have the shortest tenure in the C-suite.
3. The role of AI to improve employee experiences.
4. How to recreate the Apple Genius Bar at work... for at-home employees.
5. How generative AI will be used in the enterprise.
6. Key questions to ask when evaluating new uses of AI.
7. How CIOs deliver strategic value and avoid being "technology traffic cops".

References in this episode:

• What happens when ChatGPT is wrong?
• Mark Settle, seven-time CIO, on AI and the Future of Work
• Workato

Darren Murph has been Head of Remote at GitLab for 3.5 years and has been a part of its rise to prominence. His leadership helped shape GitLab’s remote-first culture. GitLab went public in 2021 and has about a $7B market cap. It’s one of the leading DevOps platforms and has grown its team to more than 2k employees. Before GitLab Darren has been an entrepreneur, journalist, and author. Oh, and by the way, he holds one of the most awesome records in the Guinness Book of World Records.Listen and learn:

1. How to make work an organizational principle instead of a perk or policy
2. What a Head of Remote does... and why every company will soon hire one
3. Why there's no such thing as "hybrid" work
4. The number one mistake organizations make when transitioning to remote work
5. How remote-first teams make the most of in person team
6. How GitLab uses the personal "readme" to help remote employees get to know each other
7. How to Zoom happy hours with "community service hours"
8. How Darren earned his place in the Guinness Book of World Records

References in this episode...

• Matt K. Parker on AI and the Future of Work
• Darren Murph on Twitter
• Chase Warrington, Head of Remote at Doist
• How voice assistants are helping the elderly age in place
• ElliQ, the voice assistant from Intuition Robotics

Today's episode first appeared on Peter Scott's (excellent!) AI and You podcast.Peter Scott and David Wood are two of the most recognized AI futurists. Both are respected authors, speakers, and visionaries. Peter is a popular TEDx speaker and long-time NASA engineer. David was recently named one of the "top 100 most influential people in technology".Today's discussion is a must-listen in which we discuss the future of technology, the future of work, and the future of humanity. In this one, Peter hosted and the three of us had a round table discussion about everything from generative AI to sentience. Let us know what you think after listening. Our DMs are open on Twitter and LinkedIn.Listen and learn...

1. Where AI won and lost in 2022
2. Our predictions for AI in 2023
3. What will the impact of ChatGPT be on the future of technology
4. What tasks are best-suited for generative AI
5. How we'll regulate generative AI when it spews nonsense
6. What is artificial general intelligence (AGI) and when we'll achieve it
7. What is sentience and are today's bots sentient?
8. How and where the US AI Bill of Rights falls short vs. AI regulation in the EU
9. What we should be doing to systematize the practice of responsible AI

References in the episode:

• Peter Scott on AI and the Future of Work
• Eric Olson from Consensus on AI and the Future of Work
• Michael Osterrieder from vAIsual on AI and the Future of Work
• Jim Lawton from Zebra on AI and the Future of Work
• Gary Bolles on AI and the Future of Work
• Meta's Galactica bot failure

We’ve met some brilliant product minds on this show over the years. If you’re a long-time listener you hopefully enjoyed discussions with legends like Phil McKinney, former CTO of HP, and Philippe Cases, founder and CEO of Topio Networks, among others. Today’s guest belongs on that list. Rich and I first met when he was starting UserVoice around 2010 and I was at ServiceNow. I love his approach to innovation. He pioneered the idea that listening to customers can be as easy as adding a feedback tab to every web page back when all that existed were clunky survey tools. Today, thousands of sites use the widget he invented. He’s now out to make meetings more productive by helping attendees focus on conversations while an app transcribes them and offers simple buttons to annotate what’s happening. It’s obvious once you’ve used Fathom that this is the future of meetings.

Rich White is not only a serial innovator but also a repeat entrepreneur who has raised from a group of exceptional investors over the years and was part of the YC Winter 2021 batch. Enjoy!Listen and learn...

1. As a product expert and innovator, how to know when you've found "an itch worth scratching"
2. What is "product-market fit" and how to know when you've achieved it
3. What is a viral coefficient and how do you calculate it
4. How the "jobs to be done" framework led Rich to develop the key feature of Fathom
5. The hardest problem Fathom has solved... has nothing to do with voice transcription
6. How Fathom trains developers to practice responsible AI

References in this episode:

• Project Linchpin from the US Army is centralizing more than 685 AI projects
• Phil McKinney on AI and the Future of Work
• Philippe Cases on AI and the Future of Work
• Fathom

Special episode this week! We recorded two live discussions from Turing's BOUNDARYLESS "Future of Work" event in San Francisco. In the first, Rani Mavram, Complete.so CEO, discusses using data to transform compensation policies from being a liability to an asset for high-growth companies. In the second, Ankit Jain, Aviator CEO, discusses using automation to improve developer productivity for remote-first engineering teams.Listen and learn...From Rani Mavram:

1. Why compensation policies have an outsize impact on employee engagement
2. What's required to make compensation plans transparent
3. The difference between compensation plans and "total reward" packages
4. Where innovation is happening in the field of employee compensation

From Ankit Jain:

1. How to make remote-first engineering teams successful
2. Using automation to improve developer productivity
3. How startups can replicate the developer experience at Google and Facebook
4. The future of generative AI and GitHub Copilot in assisting human developers

References in today's show:

• Turing's BOUNDARYLESS event
• Complete.so for compensation transparency
• Aviator to improve developer productivity

Merve Hickok is one of the most recognized thought leaders in the emerging field of AI ethics. Merve is the founder of AIethicist.org and Lighthouse Career Consulting. Her work is at the intersection of AI and data ethics along with social justice and DEI policy and regulation.

Merve was recently listed among the top 100 most brilliant women in AI ethics and in the past she lectured at the University of Michigan’s School of Information on Data Science ethics. Merve’s at the forefront of this emerging field that will define how we live and work for the next several decades. This is an important conversation. Enjoy!

Listen and learn… 

1. What led to Merve founding AIEthicist.org
2. How the AI ethics conversation has evolved over the past year 
3. What the White House got right (and wrong) in the blueprint for an AI Bill of Rights 
4. What responsible AI means to Merve 
5. Why regulation doesn’t necessarily constrain innovation 
6. How AI policy and regulation are different around the world 

References in this episode... 

• Why Meta’s newest LLM survived only three days online
• Jonathan Frankle on AI and the Future of Work
• Rene Morkos from ALICE Technologies on AI and the Future of Work
• Panos Siozos from LearnWorlds on AI and the Future of Work
• Paddy Padmanabhan from Damo Consulting on AI and the Future of Work

Emmanuel Turlay spent more than a decade in engineering roles at tech-first companies like Instacart and Cruise before realizing machine learning engineers need a better solution. Emmanuel started Sematic earlier this year and was part of the YC summer 2022 batch. He recently raised a $3M seed round from investors including Race Capital and Soma Capital. Thanks to friend of the podcast and former guest Hina Dixit from Samsung NEXT for the intro to Emmanuel.

I’ve been involved with the AutoML space for five years and, for full disclosure, I’m on the board of Auger which is in a related space. I’ve seen the space evolve and know how much room there is for innovation. This one's a great education about what’s broken and what’s ahead from a true machine learning pioneer.

Listen and learn...

1. How to turn every software engineer into a machine learning engineer
2. How AutoML platforms are automating tasks performed in traditional ML tools
3. How Emmanuel translated learning from Cruise, the self-driving car company, into an open source platform available to all data engineering teams
4. How to move from building an ML model locally to deploying it to the cloud and creating a data pipeline... in hours
5. What you should know about self-driving cars... from one of the experts who developed the brains that power them
6. Why 80% of AI and ML projects fail

References in this episode:

• Unscrupulous users manipulate LLMs to spew hate
• Hina Dixit from Samsung NEXT on AI and the Future of Work
• Apache Beam
• Eliot Shmukler, Anomalo CEO, on AI and the Future of Work

Kevin Mulcahy, co-author of the Future Workplace Experience, has been thinking and writing about the future of work since 2016. Six years ago the future of work was dramatically different. Reading Kevin’s book makes him seem like a clairvoyant who predicted the future. 

In addition to being a successful author Kevin is a sought after speaker on all topics related to the future of work and workplace trends. In the past, he also lectured on entrepreneurship at Babson College.Listen and learn:

1. What HR teams need to know about delivering great employee experiences
2. How Airbnb created a culture of measuring and improving the employee experience
3. What are progressive employers doing to make the transition back to office work easier
4. The three "soft leadership" questions every manager should get great at asking
5. How to measure the quality of employee experiences
6. How AI can be used to detect changes in tone in employee engagement
7. Where to start when using AI to improve the employee experience
8. How the metaverse will improve remote work

References in this episode:

• Twitter boss Elon Musk fires the entire ethics team as one of his first acts of "leadership"
• Charlene Li on AI and the Future of Work
• Gary Bolles on AI and the Future of Work
• Mark van Rijmenam on AI and the Future of Work
• Burn In: A Novel of the Real Robotic Revolution by P.W.  Singer and August Cole

Today’s guest is the co-founder and CEO of vAIsual, the company pioneering the use of generative AI to create synthetic stock media. All of those photos you see online and in print publications of people promoting products usually are human models posing in generic ways. Their pictures are sold by companies like Getty Images in marketplaces that are inefficient and limited in scope. Michael Osterrieder and his partner Nico are legends in the world of stock media who realized there’s a better way. They created what they call an algorithmic camera and launched vAIsual last year to scratch their own catch. Michael is a serial entrepreneur and photographer based in Budapest and he’s out to test the limits of generative AI.Listen and learn:

1. How growing up listening to heavy metal inspired Michael's career in visual media
2. What are the challenges of using generative AI to create synthetic stock images of people
3. How visual media content creation has evolved
4. The ethics of generative AI
5. What Michael describes as "the biggest art heist in history"
6. How vAIsual extends human photos using machine vision and human labeling
7. Can an AI be the owner of copyrighted material it produces?
8. What is the definition of consciousness?

References in this episode...

• AI has a burnout problem
• Eric Olson from Consensus on AI and the Future of Work
• Jonathan Frankle on AI and the Future of Work
• Michael's whitepaper about vAIsual

Otto Soderlund co-founded Speechly in 2016 with Hannes Heikinheimo in their hometown of Helsinki. He believes voice should be a first-class citizen for all apps and making it easy for developers to add voice support from any platform will unlock new innovation.

Speechly is a member of the YC Winter 22 batch. Otto and I recently co-presented at the VOICE22 event in Washington DC although I presented remote so this is the first time we’re actually meeting. I heard good things about his talk so I was eager for this discussion. It didn't disappoint.

Listen and learn...

1. Why voice is the new app and what it means to develop "voice-first" apps
2. How RAIN Agency uses Speechly to help auto technicians use voice assistants to fix cars
3.  How to accurately detect and transcribe speech when dealing with common challenges like background noise and accents
4. When speech detection achieved "superhuman" levels of accuracy
5. How Speechly combines speech recognition with natural language understanding (NLU) on the local device
6. How Otto thinks about exercising responsible AI
7. Why "voice technology won't exist as a separate field in a decade"

References in this episode...

• Responsible AI has a burnout problem
• Alex Capecelatro from Josh.ai on AI and the Future of Work
• Krish Ramineni from Fireflies on AI and the Future of Work
• The Speechly demo site

Jonathan Frankle, incoming Harvard Professor and Chief Scientist at MosaicML, is focused on reducing the cost of training neural nets. He received his PhD at MIT and his BSE and MSE from Princeton.

Jonathan has also been instrumental in shaping technology policy related to AI. He worked on a landmark facial recognition report while working as a Staff Technologist at the Center on Privacy and Technology at Georgetown Law.

Thanks to great guest Hina Dixit from Samsung NEXT for the introduction to Jonathan!

Listen and learn...

1. Why we can't understand deep neural nets like we can understand biology or physics.
2. Jonathan's "lottery hypothesis" that neural nets are 50-90% bigger than they need to be...but it's hard to find which parts aren't necessary.
3. How researchers are finding ways to reduce the cost and complexity of training neural nets.
4. Why we shouldn't expect another AI winter because "it's now a fundamental substrate of research".
5. Which AI problems are a good fit for deep learning... and which ones aren't.
6. What's the role for regulation in enforcing responsible use of AI.
7. How Jonathan and his CTO Hanlin Tang at MosaicML create a culture that fosters responsible use of AI.
8. Why Jonathan says "...We're building a ladder to the moon if we think today's neural nets will lead to AGI."

References in this episode...

• The AI Bill of Rights
• MosaicML
• Jonathan's personal site

Eric Olson, CEO and co-founder of Consensus, is a collegiate athlete turned data scientist turned entrepreneur who needed faster access to reliable data while working at DraftKings. Consensus is a search engine that uses a large language model to find answers in peer-reviewed research articles. Eric's living proof that the best entrepreneurs start by solving a problem they've encountered. Hear how Eric's scratching his own itch.Listen and learn...

1. Why Google isn't the answer for scientists seeking evidence-based answers online
2. Why a business model that relies on ads can't solve the "unbiased answer" problem for researchers
3. How Consensus addresses the problem of conflicting information online from credible resources
4. How to use labels to improve search retrieval accuracy... without introducing bias into results
5. How to use extractive large language models (LLMs), to extract relevant portions of documents and match them to NLP questions 
6. Why generative AI like GPT-3 can't answer "what's the consensus opinion out there" when multiple potential answers exist
7. Who is responsible if Consensus delivers answers that lead to harmful outcomes
8. What Eric learned as a division I NCAA athlete (Go Wildcats!) that has helped him as a high-tech entrepreneur

References in this episode:

• musk-shows-off-humanoid-robot-prototype-at-tesla-ai-day.html">Elon Musk launches the Optimus bi-pedal robot at AI day
• Dan Grunfeld, Stanford athlete and Lightspeed partner, on AI and the Future of Work
• Consensus

Mona Akmal, CEO of sales intelligence platform Falkon, is the outspoken co-founder behind an emerging leader in a hot space. Mona migrated to the United States at age 20 with a CS degree and little else. She had an impressive 12-year run as a product leader at Microsoft where she helped scale OneDrive and Office. She subsequently led product and technology organizations at places like Code.org and Amperity. Two decades later, Mona’s the CEO of Falkon AI, an intelligence platform for go to market teams. Falkon recently raised $16M from a group of A-list investors that includes Greylock and Madera among others.Listen and learn...

1. Why Mona's philosophy revolves around two words: "efficiency" and "excellence"
2. What makes a standout sales rep great.
3. How do find signal in noisy sales and marketing data
4. How many touches are required from stage one to closing a B2B deal
5. How to fix the CRM data hygiene problem
6. Why econometrics approaches perform better than machine learning to solve the "small data problem"
7. Why "everyone needs to be coached and nobody needs to be managed"
8. Mona's (legendary) mental health advice to entrepreneurs

References in this episode...

• Barr Moses from Monte Carlo on AI and the Future of Work
• Derek Steer from Mode on AI and the Future of Work
• Peter Fishman from Mozart Data on AI and the Future of Work
• Stephen Messer from  Collective[i] on AI and the Future of Work 
• Kamal Ahluwalia on AI and the Future of Work
• Leading scientists fear AI could lead to nuclear war by the end of the century

Hina Dixit, venture capitalist leading AI investing at Samsung NEXT, grew up in a small town in India from humble beginnings. She couldn’t afford a Starbucks coffee and graduated with significant student debt… which fueled her passion for mentoring and coaching as she became financially independent. Prior to Samsung NEXT, Hina was an Apple engineering leader who helped launch two-factor authentication and other core iOS technologies. Hina’s a reluctant venture investor having always been a builder. A mentor from Homebrew encouraged her to pursue investing and she’s now passionate about finding and funding the next generation of AI and web3 entrepreneurs.Listen and learn… 

1. How Hina overcame institutional biases to achieve success in engineering leadership roles and venture investing 
2. How being trusted with money at a young age by her father helped Hina become independent and confident in her career 
3. The challenges Hina faced transitioning from a builder at Apple to an investor at Samsung NEXT 
4. What Hina looks for when investing in AI and web3 startups 
5. Where there are opportunities for innovation in web3 and metaverse infrastructure 
6. What will prevent Big Tech from centralizing the decentralized web 
7. How Hina thinks about responsible AI when evaluating new investments 
8. How and when entrepreneurs should engage corporate venture capital (CVC) firms 
9. The AR/VR technology Hina wants to invest in… her inbox is open :) 

References in this episode: 

• Paul Lee, Synesis One CEO, discusses AI, web3 and crypto for gaming on AI and the Future of Work 
• Krishna Gade, Fiddler CEO, discusses AI explainability on AI and the Future of Work 
• Barr Moses, Monte Carlo CEO, discusses data pipeline monitoring on AI and the Future of Work 
• Bindu Reddy, Abacus AI CEO, discusses training and managing data models on AI and the Future of Work 
• How Jack Clark is incorporating AI ethics into new AGI research

Rana Gujral, CEO of Behavioral Signals since 2018, joined the company after a distinguished tech career growing companies like Logitech, TiZE, and Cricut. Behavioral Signals uses emotion and behavioral science to help contact center agents deliver better service. Rana and the team are on a mission to improve customer interactions by using signals other than the spoken word to understand exactly what they need based on indicators like voice tone and pitch.Listen and learn...

1. How to train AI models on past service interactions and outcomes to determine which agents should speak to which customers
2. How to use deep learning and NLP to process non-speech behavior signals like intonation, pitch, and tonal variance
3. How behavior signals can be used to predict stress, duress, and propensity to buy or pay
4. How to achieve high levels of prediction accuracy without processing "the spoken word"
5. Why tone and pitch are better indicators of sentiment than actual words across any language 
6. How to compete with Google/Microsoft/Amazon for data when building an AI-first conversational intelligence product
7. The biggest opportunity Rana sees to use AI to help humans live better lives

References in this episode:

• Mahesh Ram from Solvvy (now Zoom) on AI and the Future of Work
• Gadi Shamia from Replicant on AI and the Future of Work
• How personalization algorithms work in your social feeds
• Behavioral Signals

Ahmed Elsamadisi built the data infrastructure at WeWork before realizing every company could benefit from his team’s innovation. Traditional star schemas aren’t the best way to manage data. Ahmed instead pioneered a new approach using a single-table column model better suited for real questions people ask. He launched Narrator in 2017 to make it easier to turn data questions into answers and has since raised $6.2M from Initialized Capital, Flybridge Capital Partners, and Y Combinator. Ahmed received his BS in Robotics from Cornell. Hear from a pioneer (and tech provocateur) how new data wrangling techniques are making it easier for mere mortals to get more value out of their data.Listen and learn…

1. How a roboticist who got his start building self-driving cars and designing missile defense systems ended up redefining how data is stored
2. Why traditional approaches that require SQL to access data are broken
3. How a single-column schema eliminates the complexity of joining systems and tables
4. Why it’s easier to tell better stories with data using temporal relationships extracted from customer journeys
5. Why Snowflake, Redshift, and BigQuery are really all the same… and data modeling is the place to innovate 
6. What it means to replace traditional tables with activities… and why they’ll eliminate the need for specialized data analysts 
7. How to reduce data storage costs by 90% and time to generate data insights from weeks to minutes 
8. Why data management vendors are responsible for bad decisions made using your data 
9. What is data cleaning and how you should do it 
10. What is a racist algorithm 
11. Why querying data with natural language will never work 
12. Is the WeCrashed version of Adam Neumann’s neuroticism accurate? Hear from someone who lived it... 

References in this episode:

• Google’s LaMDA isn’t sentient
• Chandra Khatri from Got It AI on AI and the Future of Work 
• Derek Steer from Mode on AI and the Future of Work 
• Barr Moses from Monte Carlo on AI and the Future of Work 
• Peter Fishman from Mozart Data on AI and the Future of Work 
• Ahmed on Twitter 

Seth Earley is a Chemist by training and an expert on AI. Specifically, how AI is used to improve knowledge management. In fact, he wrote the book on the topic titled “The AI-Powered Enterprise” in which he explains the importance of ontologies when applying AI. Seth is the CEO of Earley Information Science. He has been advising companies on technology strategy since 1994 and is currently focused on AI and knowledge engineering. Listen and learn: 

1. Seth’s contribution to AI history… including the term he coined that was co-opted by former IBM CEO Ginni Rometty 
2. Why all AI is a data (and information architecture) problem 
3. How the Applied Materials field services team reduced time spent finding information by 50% with knowledge engineering and ontologies 
4. Why proper information architecture is required for virtual agents to reduce call volume and help live agents 
5. What has changed since Seth first published his AI book in 2020 
6. The benefits of semantic search vs. traditional keyword search 
7. Where to start with a knowledge management strategy 
8. Why “data scientists spend more time being data janitors” 
9. How to mitigate the impact of bias in AI training data 

References in this episode: 

• How AI can detect employee burnout
• The Innovation Delusion on Amazon 
• Earley Information Science
• The AI-Powered Enterprise on Amazon 
• Kevin Dewalt, Prolego CEO, on AI and the Future of Work

Peter Scott, author, TedX speaker, and futurist, worked at NASA’s JPL laboratory after receiving his Masters Degree in Computer Science from Cambridge. Raising kids made him realize the potential impact of AI to do both good and harm. He left NASA and switched careers to feel confident he was doing all he could to secure their future. He recently published Artificial Intelligence and You after publishing Crisis of Control five years back. 

Listen and learn: 

1. When will we achieve artificial general intelligence (AGI)… and is that the right goal for the AI community? 
2. Why we weight the potential of AI doing harm about five times as much as the potential for it doing good. 
3. What’s the biggest global problem AI might solve in the near term. 
4. How DeepMind’s AlphaFold protein folding technology could change humanity. 
5. What does it mean to be human in an era when machines can do more tasks historically reserved for humans? 
6. Why Peter blames Big Tech for “breaking” democracy. 
7. What Peter expects will be AI’s greatest achievement in the next decade. 
8. Why the evolution of a digital race hinges on global economic incentives.

References in this episode: 

• Peter’s site: humancusp.com
• Peter’s podcast: AIandYou.net
• Reducing “radicalization pathways” in social media feeds
• Stuart Russell’s AI textbook  
• Dr. Mark van Rijmenam on AI and the Future of Work 
• Peter Scott’s homage to Monty Python… and how it relates to AI 

Kia Kokalitcheva, Axios tech reporter, is a Silicon Valley native who writes about tech news and culture. Among other things, she co-authors the popular Pro Rata newsletter (over 200k subscribers) with Dan Primack. Kia has covered many of the most iconic tech stories of the past decade as a writer at Fortune and VentureBeat prior to Axios which was just acquired by Cox Enterprises. Kia recently wrote about Adam Neumann’s new company, Flow. Hear Kia’s perspectives on how Flow could transform living like WeWork transformed working… and why she’s not scared that bots may take her job. 

Listen and learn… 

1. How Adam Neumann of WeWork fame raised $350M at a $1B valuation from A16Z for his new company Flow… before launching  
2. Kia’s proudest moment as a journalist 
3. What the acquisition of Axios by Cox Enterprises means for journalism 
4. How Flow may be more than the reincarnation of WeWork’s failed WeLive experiment 
5. As a culture, are we ready for communal living? 
6. What is the future of company perks… are the days of on-site dry cleaning numbered? 
7. How the generational shift is impacting cultural norms in the workplace 
8. What tasks bots will never do better than live journalists 

References in this episode: 

• How AI is transforming journalism according to The Knight Foundation 
• Gary A. Bolles discusses the WorkNet on AI and the Future of Work 
• Mark van Rijmenam, The Digital Speaker, on AI and the Future of Work 

Deon Nicholas, Forethought Co-Founder CEO, grew up in inner city Toronto stocking shelves in a pharmacy before learning to code at an early age. He started Forethought in 2017 after learning the value of answering customer questions working for companies like Facebook and Pure Storage. Deon has since raised $92M from an exceptional group of investors including funds like Steadfast Capital and NEA plus celebrities including Gwyneth Paltrow, Ashton Kutcher, and Robert Downey Jr. Deon won the TechCrunch Disrupt Battlefield startup competition in 2018 and is a member of the Forbes 30 under 30. He’s also a mentor and advisor to founders of color. Listen and learn...

1. How AI connects customers to the right agents then indicates the likelihood of a support interaction escalating
2. How to use historical data to help live agents fix problems faster
3. The evolution of chatbots from decision trees to AI
4. How to combine generic language models with domain-specific data to increase the accuracy of NLP
5. How to solve the problem of bias encoded in data
6. How GANs, generative adversarial networks, work
7. Why ML pipelines need to be monitored like web apps

References in this episode...

• Forethought
• Deon on Twitter
• Forward, the Forethought customer event
• Krishna Gade from Fiddler on AI and the Future of Work
• Monotonic selective risk may solve the AI bias problem

Jim Lawton, VP and GM of Robotics Automation at Zebra Technologies, met the founder of Roomba, Rodney Brooks, at MIT nearly three decades ago. It inspired a lifetime passion for  robots that help humans. Since then, he has influenced generations of robotic automation technology at companies from Rethink Robotics to Zebra Technologies. This is a fascinating discussion that will make you reconsider what robots can do and why humans shouldn't feel threatened by them. Listen and learn...

1. How Jim cultivated a passion for robots... and why that makes him "the cool dad"
2.  How innovation in robotic technology is helping AMRs, autonomous mobile robots, perform more human-like tasks with less training
3. Which "dirty, dull, dangerous" tasks are the best candidates for robotic automation 
4. How new training techniques are reducing the time required to train a robot from 300 hours to a fraction of that  which "democratizes automation"  
5. What's required to keep humans safe from robots
6. How supplementing humans with robots for a task like picking items from warehouse shelves using machine vision saves 12-15 miles of walking per day while increasing accuracy
7. How techniques like SLAM and machine learning are making it easier to program robots to do more complex tasks more accurately with zero or minimal coding
8. Which new careers will be created by industrial robots... and which will be eliminated
9. Two quick ways to know if a factory using robots and humans is safe 
10. Why Jim's passion is using robots to help people be their best selves

References in this episode:

• The Zebra blog
• Tiernan Ray discusses bot sentience on AI and the Future of Work
• Is Google's LaMDA sentient?
• Machines will out-perform humans in all tasks within 45 years... which is a good thing for us

Kamal Ahluwalia and the Eightfold team set out to find the right career for everyone in the world. Six years later after having raised more than $200M from a legendary group of investors and built a talented 600-person team, they’re well on their way. Kamal joined Eightfold as President in 2018 from a successful tech career at companies like Model N and Selectica. Hear Kamal share his vision for how to use data and AI to help employees upskill, reskill, and ultimately find careers they love. 

Listen and learn…

1. How Eightfold operationalizes the bold vision to find “the right career for everyone in the world" 
2. What has helped Eightfold scale to support customers in 140 countries and 19 languages
3. How an AI HR platform helps with upskilling for internal mobility but also with hiring and talent-skill matching
4. Why legacy HR tech software failed by focusing on “compliance vs. employee needs” 
5. Why automation won’t eliminate jobs… but every job will change as a result of AI 
6. How understanding human potential starts with understanding data stored outside HCM in “systems of work” like CRM and ITSM 
7. How to mitigate the impact of biased data to use AI to achieve inclusion and diversity goals
8. How AI can identify roles where employees are likely to succeed… even when they have no experience performing skills they require 
9. What are the ethical implications of using AI to hire and promote employees 

References in this episode: 

• OneTen.org and the role of Eightfold in its formation 
• Renee Steenvorden from Randstad on AI and the Future of Work 
• Giselle Mota from ADP on AI and the Future of Work 
• Ashu Garg from Foundation Capital on AI and the Future of Work 
• The BigScience BLOOM LLM

Ben Brennan, former guest, accomplished author, and QSTAC CEO, guest hosts today's "turn the tables" episode... and interviews Dan Turchin, PeopleReign CEO. Learn about Dan's vision for augmenting human intelligence with machine intelligence and how AI will be used to give the next billion employees back an hour a day.Listen and learn...

1. The origin story behind this podcast
2. What's required to use AI to improve employee experiences 
3. How many new jobs will be created by AI in the next five years according to The World Economic Forum
4. The right way for investors to identify talent and catalyze innovation
5. How Ben learned the value of human-centric AI from his days at Yahoo, Box, and Twitter

References in this episode:

• Mark Settle, serial CIO, on AI and the Future of Work
• Dr. Mark van Rijmenam, The Digital Speaker, on AI and the Future of Work
• Rory O'Driscoll from Scale Ventures Partners on AI and the Future of Work
• Ashu Garg from Foundation Capital on AI and the Future of Work 
• Glenn Solomon from GGV on AI and the Future of Work 
• The great Katie Stanton, PeopleReign investor from Moxxie Ventures

Gadi Shamia, Replicant CEO and co-founder, has been delivering innovation to help customers have better service experiences for more than a decade. He helped grow and sell Echosign to Adobe for $400M in 2011 then went on to lead Talkdesk which most recently raised $230M at a $10B valuation. Gadi's a serial entrepreneur and a deep thinker who believes in the power of AI to make people better. Listen and learn:

1. Why we hate calling customer support... and how AI is making the experience better
2. Why automation beyond IVR is saving contact centers
3. What happens when AI makes bad decisions
4. When it's ok to "nudge" users to work with the bot... even when they ask for a human
5. The ethical implicatio ns of bots pretending to be human 
6. What new careers  will be created when call center agents are replaced by bots

References in this episode:

• Replicant on Twitter
• The Replicant blog
• The Open Ethics AI initiative
• Krishna Gade from Fiddler on AI and The Future of Work
• John Oliver's riff on automation

Krish Ramineni, Fireflies CEO and Microsoft alum, learned the value of NLP working with Skype and Office as a Product Manager. He set out to solve a problem he had: note-taking in meetings and following up afterward. Fireflies has been used by more than 60,000 organizations to make meetings more efficient. Krish has raised nearly $20M from an A-list group of investors including Canaan Partners and Khosla Ventures. Listen and learn...

1. The evolution of speech recognition technology in the enterprise
2. How Krish and the team build an AI voice assistant that joins  meetings in 100 countries every day
3. How to start with 85% ASR (automated speech recognition) accuracy and make it better using AI
4. How to mitigate the impact of biased training data where foreign accents and uncommon speech patterns are underrepresented
5. Who owns voice transcripts used to train AI models
6. How being recorded changes participant behavior in meetings
7. The future of "voice-first" computing

References in this episode:

• Krishna Gade from Fiddler discusses AI explainability
• Fireflies on Twitter 
• A whole breast, AI-based ultrasound system was cleared by the FDA to improve mammogram accuracy
• Dentists now use AI to improve the accuracy of spotting cavities

Joel Eagle, McDonald's Senior Director of Technology and Architecture, started his career in healthcare and logistics before being promoted to technology leadership roles at one of the world's most iconic companies. Joel and his team manage the cloud infrastructure that powers 40,000 restaurants for two million employees... and helps serve happiness in 120 global markets to the equivalent of the  world's population every 100 days. The technology that makes McDonald's work is phenomenally complex. Joel makes it sound simple. Hear from the expert. Oh, and stick around to the end for McDonald's fun facts!Listen and learn...

1. How Joel channels Ray Kroc's vision when architecting systems: "restaurants should run themselves... it should be as simple as a shoebox with money going in and going out."
2. Why Joel says "if it's easier for the crew it's better for the consumer."
3. How AI, wearables, IoT, and AR are all parts of the McDonald's technology vision.
4. Why the shift supervisor at a McDonald's restaurant has one of the hardest jobs in the world. 
5.  The anatomy of a McDonald's restaurant: "...they're mini factories run by a server."
6. How AI is improving the drive-thru experience and personalizing the dining experience.
7. What's required to support the McDonald's app which generates 16% of the company's revenue and is the world's most downloaded food ordering app.

References in this episode...

• McDonald's by the numbers
• Meta Research is improving NLP accuracy with less training data by using our understanding of how humans learn languages
• Giselle Mota, TEDx speaker and top 100 "Future of Work" thought leader, on AI and the Future of Work

1. What Ben learned managing 100 people and supporting 15,000 employees at Yahoo
2. How the culture at Pivotal Labs inspired Ben's philosophy on quantifying the employee experience
3. How Ben convinced a former Apple leader why QSTAC is better than NPS
4. Why CSAT scores don't actually correlate with how satisfied employees are at work
5. How the principles of design.org/literature/article/what-is-design-thinking-and-why-is-it-so-popular">Design Thinking can be used to run IT
6. What IT must do to avoid being "Uber-ed" like the taxi industry

• Dion Hinchcliffe on AI and the Future of Work
• Tim Crawford on AI and the Future of Work
• Matt K. Parker on AI and the Future of Work
• O'Reilly's 2021 AI adoption in the enterprise survey
• QSTAC

Francois Candelon, Managing Director at the BCG Henderson Institute, has spent 30 years researching how companies adopt modern technology.  His research spans business, technology, economics, and science. Francois is a popular speaker, author, and advisor who has been featured at events including Mobile World Congress, TED@BCG, Politico AI Summit, and Wuzhen Internet Conference. Francois is also a leader on BCG's GAMMA AI@Scale team. Listen and learn...

1. The one company Francois says best illustrates how AI can transform legacy industries
2. Why "artificial intelligence" isn't really "intelligent"
3. What is an "AI strategy"... and what are the four questions to ask to define yours
4. How a fintech company in the UK reduced costs to transfer money by 90% with AI
5. What's required to earn the public's trust in AI
6. Why every company should be required to have a "social license" to use AI

References in this episode...

• Fortune article on human-machine collaboration by Francois
• Francois' "BCG Expert" profile
• Dr. Eric Daimler, Obama's AI authority, on AI and the Future of Work
• The McKinsey "AI in 2020 Survey"

Stephen Messer, founder of Collective[i], was an attorney and teacher before discovering his passion for entrepreneurship. He started LinkShare (acquired by Rakuten in 2005) which made it possible to pay for clicks on the web. He changed how the web works and now he's using AI to change the world of B2B sales. The world needs more visionaries like Stephen. Hear what fuels him and learn about his process for disrupting legacy industries.Listen and learn...

1. The four words that define what all the best entrepreneurs do better than everyone else
2. Why sales is the only job function where "30% productivity is the norm"
3. What's required to use AI to help B2B sales people
4. How to use RPA to automatically update CRM systems
5. How Stephen's winning against Salesforce, Microsoft, and HubSpot
6. What to look for in a mentor

References in this episode...

• The Collective[i] blog
• Stephen on Twitter
• language-model-palm-scaling-to.html">Google PaLM
• Mahesh Ram, Solvvy CEO (acquired by Zoom), on AI and the Future of Work

In this special episode, we unpack the controversy surrounding the sentient chatbot that "worries about its future". Google engineer Blake Lemoine published a transcript of a conversation with the chatbot LaMDA that generated strong reactions from technologists and AI ethicists. It conjured images from science fiction movies that always capture the public imagination.Tiernan Ray, ZDNet writer, accomplished tech journalist,  and good friend of the podcast, joined host Dan Turchin to reflect on the story based on his analysis of the 5,000-word LaMDA transcript.Listen and learn...

1. What will it be like to co-habit a world with thinking machines?
2. What does it mean for an AI to be sentient? Why should we care?
3. Should AI be protected under the 13th amendment?
4. How do we know LaMDA's not sentient from the transcript?
5. What are the ethical implications of developing sentient bots?
6. Did Google act responsibly in developing a bot that is sentient-like?

References in this episode...

• Tiernan's analysis of the LaMDA transcript
• Melanie Mitchell on MSNBC
• Blake Lemoine's interview with Steven Levy in Wire 
• Alan Turing's Imitation Game

Kevin Dewalt, CEO of Prolego, built his first neural net at Stanford in 1995 after graduating from the U.S. Coast Guard Academy. He popularized the term "AI abundance" to describe the path of exponential technologies and how AI adoption is five years from becoming mainstream. He now applies 25 years of studying AI to help organizations embrace the future. Listen and learn...

1. What every company needs to know to succeed with AI.
2. How the most successful organizations approach AI investments.
3. Why Kevin says: "...we haven't had a single project where we've used AI to eliminate jobs."
4. What Kevin feels is the most disruptive field within AI research.
5. Practical applications of NLP and large language models (LLMs) 
6. Kevin's contrarian view on AI ethics

References in this episode:

• The world's first AI comic book
• Kevin's book: Become an AI Company in 90 days
• Kevin's company: Prolego
• Snorkel to automate data labeling
• Andrew Yang on AI
• "D" Das, Founder and CEO of Sorcero, on AI and the Future of Work

Giselle Mota, Future of Work principal at ADP, overcame dyslexia and discovered passions for math and AI. Her parents immigrated from the Dominican Republic and taught Giselle the power of perseverance. Now she speaks frequently to global audiences about the importance of using AI responsibly to hire and nurture talent.Listen and learn...

1. How AI accelerates the process of learning new skills
2. How to mitigate the impact of bias in automated decision-making
3. The dangers of using facial recognition in recruiting and hiring processes
4. How to design organizations that celebrate cognitive diversity
5. How to optimize hiring processes to avoid confirmation bias
6. How many jobs will be created by AI before 2025 according to the World Economic Forum
7. Giselle's coaching for females and under-represented minorities in STEM fields

References in this episode:

• Your $250 discount from Hello Landing using Giselle's promo code: giselle_itg
• Bernard Marr, Futurist
• Joy Buolamwini, AI social justice advocate
• Bryan Talebi from Ahura AI on AI and the Future of Work
• Kai Nunez from Salesforce on AI and the Future of Work